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The AI and LLM Engineer's Reading List for 2026 (10 Books That Matter)

2026-04-13T06:41:00.000-07:00

Hello Guys, The AI world is moving ridiculously fast.

New models, new frameworks, new tools — every week there’s something new for AI engineers to learn. But if there’s one thing that consistently separates great engineers from the rest, it’s strong fundamentals.

And for that, books still beat everything else.

Over the past few months, I’ve been diving deep into some of the best books on AI engineering, LLMs, and production AI systems. These are not just theoretical reads — they cover everything from building LLMs from scratch, to designing scalable ML systems, to deploying AI applications in production.

In this newsletter, I’m sharing 10 AI and LLM Engineering books I’m reading in 2026 — books that every developer, ML engineer, or AI enthusiast should have on their radar.

These include fantastic titles from experts like Paul Iusztin , Chip Huyen, Sebastian Raschka, PhD , Maxime Labonne , Louis-François Bouchard , Louie Peters and others who are shaping how modern AI systems are built.

If you want to learn how to:

Build LLM-powered applications
Design scalable AI systems
Understand prompt engineering and agentic AI
Deploy LLMs in production

then these books are an excellent place to start.

Let’s dive into the list.

10 Must-Read Books for AI and LLM Engineers in 2026

Without any further ado, here is a list of the 10 Best Books to Learn AI and LLM Engineering in 2026. This includes books on AI, Machine Learning, and Large Language Models.

If you’re serious about becoming an AI engineer or working with LLMs, this list is your roadmap.

1. AI Engineering by Chip Huyen

This is the first book you should read on AI Engineering, and if you don’t like reading many books, then this single book is enough to learn all the skills you need to become an AI Engineer in 2026.

Chip Huyen , author of this book, brings a refreshing focus on AI systems design rather than just models.

If you don’t know, Chip has worked as a researcher at Netflix, was a core developer at NVIDIA (building NeMo, NVIDIA’s GenAI framework), and cofounded Claypot AI. She has also taught machine learning (ML) at Stanford University.

This book covers what an AI engineering stack looks like: the one that we software engineers must become experts in order to be an AI engineer.

You’ll learn how to turn machine learning models into real products --- handling data pipelines, model versioning, deployment, monitoring, and scaling.

It also covers what AI engineering is, how it differs from ML engineering, and the techniques AI engineers should be familiar with.

If your goal is to become a true AI Engineer (not just a Kaggle competition winner), this book is pure gold.

Here is the link to get this book --- AI Engineering by Chip Huyen

2. The LLM Engineering Handbook by Paul Iusztin and Maxime Labonne

This book is like an operations manual for LLM development.

It covers prompt engineering, model fine-tuning, retrieval-augmented generation (RAG), evaluation strategies, and production patterns.

The authors have real-world experience building LLM apps at scale.

Highly recommended if you want to move from “just using GPT” to designing serious LLM applications.

Here is the link to get this book --- The LLM Engineering Handbook by Paul Iusztin and Maxime Labonne

3. Designing Machine Learning Systems by Chip Huyen

This is another great book from Chip Huyen, one of my favorite authors when it comes to AI and LLM engineering

While “AI Engineering” focuses more on the systems side, this one gets into how to design and operate machine learning systems under real-world constraints like data drift, retraining, and model reliability.

You’ll start thinking like a machine learning product engineer, not just a model builder.

Here is the link to get this book --- Designing Machine Learning Systems by Chip Huyen

4. Building LLMs for Production by Louis-François Bouchard and Louie Peters

This book shows you how to actually ship Large Language Models into production environments. You’ll learn about fine-tuning, deploying, scaling, and maintaining LLMs like a real engineer.

It’s packed with hands-on advice, architecture examples, and real deployment challenges.

If you’re aiming for a career as an LLM engineer, this book should be your first read.

Here is the link to get this book --- Building LLMs for Production by Louis-François Bouchard and Louie Peters

5. Build a Large Language Model (from Scratch) by Sebastian Raschka, PhD

Sebastian Raschka is a legend in the machine learning community. This book teaches you how to build a transformer-based LLM from scratch using PyTorch, with no shortcuts.

You’ll go deep into model architecture, tokenization, attention mechanisms, and training strategies.

Perfect for developers who want to understand LLMs at the code level, not just use APIs like OpenAI’s.

Here is the link to get this book --- Build a Large Language Model (from Scratch) by Sebastian Raschka, PhD

6. Hands-On Large Language Models: Language Understanding and Generation

Jay Alammar and Maarten Grootendorst are two of the most respected names in the AI and NLP space.

This book walks you through building and fine-tuning large language models with modern tools like Hugging Face Transformers, LangChain, and more.

It’s hands-on and practical --- ideal for developers, data scientists, and ML engineers who want to build and deploy LLMs that understand and generate human language effectively.

Here is the link to get this book --- Hands-On Large Language Models

7. Prompt Engineering for LLMs: The Art and Science of Building Large Language Model-Based Applications

If you’re building AI products using OpenAI, Claude, or open-source LLMs, this book shows you how to write smarter prompts for better results.

It covers strategies like few-shot prompting, chain-of-thought, and using prompt patterns effectively.

Created by John Berryman and Albert Ziegler this book dives into the evolving art and science of prompt engineering.

A must-read for AI developers and product designers.

Here is the link to get this book --- Prompt Engineering for LLMs

8. Building Agentic AI Systems: Create Intelligent, Autonomous AI Agents that can Reason, Plan, and Adapt

Written by Anjanava Biswas and Wrick Talukdar, this book explores how to build agentic AI systems that can go beyond static outputs.

This book shows you how to create autonomous AI agents that can interact with environments, reason, make decisions, and take actions.

If you’re interested in building AI agents like Auto-GPT, BabyAGI, or LangGraph-based systems, this guide is a goldmine.

Here is the link to get this book --- Building Agentic AI Systems

9. Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs

This is a comprehensive guide to prompt engineering techniques specifically designed for generative AI systems --- including text, image, and code generation.

The book emphasizes how to write prompts that are robust, consistent, and tailored for business and production environments.

Whether you’re working with GPT, DALL-E, or other models, this Prompt Engineering book by James Phoenix and Mike Taylor will definitely help you future-proof your AI input strategies.

Here is the link to get this book --- Prompt Engineering for Generative AI

10. The AI Engineering Bible: The Complete and Up-to-Date Guide to Build, Develop and Scale Production Ready AI Systems

Thomas R. Caldwell’s AI Engineering Bible is a must-have for software engineers and tech leaders.

It goes beyond models and APIs to show you how to engineer real-world AI systems that are scalable, maintainable, and production-ready.

From architecture to infrastructure, deployment to monitoring, it covers the entire AI lifecycle. This is the playbook for anyone who wants to lead AI implementation in their organization.

Here is the link to get this book --- The AI Engineering Bible

Why You Should Read These Books?

Apart from my recommendations and several others on Reddit and HN, here are the top 5 reasons why you should read these AI and LLM Engineering books.

They’re written by practitioners who have built production AI/LLM systems.
They focus on engineering, deployment, and real-world use cases --- not just algorithms.
They don’t waste your time with outdated academic theory.
They prepare you for the future of AI and LLM work: scalable, reliable, explainable systems.
Widely recommended by professionals on Reddit and Hacker News.

Reading books is powerful, but nothing beats building things.

If you want to accelerate your learning, combine these books with a hands-on course like: LLM Engineering: Master AI, Large Language Models & Agents to get some hands-on experience on building RAG RAG-based chatbot and learning LLM by watching.

Conclusion

That’s all about the best books to learn AI and LLM Engineering in 2026. If you’re serious about mastering AI and LLM engineering in 2026 and beyond, start with these must-read AI and LLM Engineering books.

They’ll save you hundreds of hours of wasted time and help you actually build systems that work.

Want even faster progress?
If you want more fun and faster progress then you can also pair these books with hands-on projects like building your own RAG-based chatbot, fine-tuning a model on your own dataset, or deploying a real-world LLM app to the cloud.

I Tried 50+ AI Courses on Udemy: Here are The Best 5

2026-04-11T21:52:00.000-07:00

Hello guys, the AI revolution isn’t coming — it’s already here. In 2026, artificial intelligence skills have become as essential as knowing how to code was a decade ago.

Whether you’re a developer looking to build AI-powered applications, a product manager wanting to understand AI capabilities, or a professional aiming to stay relevant in an AI-driven workplace, now is the time to upskill.

The landscape has evolved dramatically. We’ve moved beyond basic chatbots to sophisticated AI agents that can reason, plan, and execute complex tasks autonomously.

Skills like prompt engineering, agentic AI development, and working with frameworks like LangChain and LangGraph are now among the most in-demand abilities in tech.

After researching 20+ of AI courses on Udemy, I’ve identified the top 5 Udemy courses that will give you practical, job-ready AI skills in 2026. These aren’t theoretical lectures — they’re hands-on courses that teach you to build real AI applications.

By the way, if you are new to AI world then I highly recommend you to start with The AI Engineer Course 2026: Complete AI Engineer Bootcamp, one of the most comprehensive resource to become an AI Engineer in 2026.

Why These AI Skills Matter in 2026?

Prompt Engineering has become the new programming. Knowing how to communicate effectively with AI models can 10x your productivity and unlock capabilities that seem like magic.

Agentic AI represents the next frontier — AI systems that can autonomously accomplish goals, make decisions, and coordinate with other agents to solve complex problems.

LangChain has emerged as the go-to framework for building production-ready LLM applications, making it an essential tool for any AI developer.

MCP (Model Context Protocol) and frameworks like AutoGen are revolutionizing how AI agents communicate and collaborate, opening doors to multi-agent systems that can tackle enterprise-scale challenges.

Let’s dive into the top 5 courses that will help you master these critical skills.

5 Best Udemy Courses to learn Essential AI skills in 2026

Without any further ado here are the top Udemy courses you can join to learn essential AI skills like Prompt Engineer, MCP, Agentic AI development, and frameworks like LangChain and LangGraph.

1. Artificial Intelligence A-Z™: Learn How To Build An AI

Best For: Complete beginners wanting a comprehensive AI foundation

This course is the perfect starting point for anyone new to artificial intelligence. It takes you from zero knowledge to building your own AI systems, covering both the theory and practical implementation.

What You’ll Learn:

Fundamental AI concepts and how AI actually works
Building various types of AI from scratch
Understanding machine learning algorithms
Creating self-improving AI systems
Real-world AI applications and use cases
Both supervised and unsupervised learning techniques

Why This Course Stands Out:

The “A-Z” format means you get comprehensive coverage without gaps in your knowledge. The instructors break down complex concepts into digestible lessons, making AI accessible even if you’re coming from a non-technical background. You’ll build actual AI projects, not just watch theory lectures.

The course balances theory with hands-on coding, ensuring you understand why things work, not just how to copy-paste code. This foundational knowledge becomes invaluable as you move into more specialized areas like prompt engineering or agentic AI.

Perfect If You’re:

New to AI and want a solid foundation
Looking to transition into AI development
Wanting to understand what’s possible with AI before specializing

Here is the link to join this course — — Artificial Intelligence A-Z™: Learn How To Build An AI

2. The Complete Prompt Engineering for AI Bootcamp (2026)

Best For: Anyone wanting to master AI communication and maximize productivity

Prompt engineering has become one of the hottest skills in 2026. This isn’t just about writing better ChatGPT prompts — it’s about understanding how to architect complex instructions, chain prompts together, and extract maximum value from any AI model.

What You’ll Master:

Advanced prompt design patterns and techniques
Creating effective system prompts for consistent results
Chain-of-thought reasoning and few-shot learning
Building prompt templates for common tasks
Debugging and iterating on prompts systematically
Model-specific optimization techniques
Ethical considerations in AI interaction

Why This Course Is Essential:

Prompt engineering is the skill that multiplies all your other AI abilities. Whether you’re building applications with LangChain or deploying agentic systems, knowing how to communicate precisely with AI models is foundational.

The bootcamp format means you get intensive, practical training with real exercises. You’ll learn techniques that work across different models — from GPT-4 to Claude to open-source alternatives. The 2026 update ensures you’re learning cutting-edge techniques, not outdated methods.

Real-World Applications:

10x your productivity with AI assistants
Build better AI-powered products
Create custom GPTs and AI tools
Optimize costs by reducing token usage
Develop AI applications that actually work reliably

Perfect If You’re:

Using AI tools daily and want to get more from them
Building AI features into products
Working as a product manager, designer, or developer

Here is the link to join this course — — The Complete Prompt Engineering for AI Bootcamp

3. LangChain — — Develop LLM Powered Applications with LangChain

Best For: Developers building production AI applications

LangChain has become the standard framework for building LLM-powered applications. This course teaches you to harness its power to create sophisticated AI systems that go far beyond simple chatbots.

What You’ll Build:

Complete LLM-powered applications from scratch
Retrieval-Augmented Generation (RAG) systems
AI agents that can use tools and APIs
Conversational AI with memory and context
Document analysis and question-answering systems
Custom chains for specific use cases

Core Concepts Covered:

LangChain architecture and components
Prompt templates and chains
Memory systems for conversational AI
Vector databases and embeddings
Integrating external tools and APIs
Building production-ready AI applications

Why LangChain Matters:

While you can technically build AI applications without frameworks, LangChain provides battle-tested abstractions that save months of development time. It handles the complex orchestration of prompts, manages conversation memory, integrates with vector databases, and provides easy tool connectivity.

The course goes beyond documentation — you’ll understand the design patterns and architectural decisions that make great AI applications. You’ll learn when to use chains versus agents, how to optimize for cost and latency, and how to handle errors gracefully.

Perfect If You’re:

A developer wanting to build AI features
Creating chatbots or AI assistants
Interested in RAG and document AI
Building internal AI tools for your company

Here is the link to join this course — — LangChain — — Develop LLM Powered Applications with LangChain

4. Building AI Agents & Agentic AI Systems via Microsoft AutoGen

Best For: Developers ready to build autonomous multi-agent systems

Welcome to the cutting edge of AI development. Agentic AI represents systems that can reason, plan, and execute tasks autonomously. AutoGen, Microsoft’s powerful framework, makes it possible to build sophisticated multi-agent systems where different AI agents collaborate to solve complex problems.

What You’ll Create:

Autonomous AI agents that accomplish goals independently
Multi-agent systems where agents collaborate
AI assistants that can use tools and execute code
Self-improving systems with feedback loops
Enterprise-grade agentic applications

Key Skills Developed:

Understanding agent architecture and design
Building agents with different roles and capabilities
Orchestrating agent conversations and collaboration
Implementing tool use and code execution
Managing agent memory and state
Debugging and monitoring agent behavior

Why AutoGen Is Revolutionary:

AutoGen represents a paradigm shift from single-model interactions to complex multi-agent orchestration. Imagine having a team of specialized AI agents — one for research, one for coding, one for testing, one for documentation — all working together on your projects.

The course teaches you to architect these systems, handle the complexity of agent communication, and build reliable systems that can tackle problems far beyond what a single AI model can handle.

Real-World Use Cases:

Automated software development workflows
Research and analysis systems
Customer service with specialized agents
Data processing pipelines with intelligent routing
Complex decision-making systems

Perfect If You’re:

Building advanced AI applications
Interested in autonomous systems
Working on AI research or innovation
Ready to push beyond basic LLM applications

Here is the link to join this course — Building AI Agents & Agentic AI Systems via Microsoft AutoGen

5. The Complete Agentic AI Engineering (2026)

Best For: Engineers wanting comprehensive coverage of modern agentic AI

This comprehensive course brings everything together — prompt engineering, LangChain, multi-agent systems, and the Model Context Protocol (MCP). It’s designed for engineers who want to master the complete agentic AI stack.

Comprehensive Coverage:

Building sophisticated AI agents from first principles
Implementing agentic workflows and patterns
Understanding and using the Model Context Protocol
Creating agents that can plan and reason
Memory systems and context management
Tool use and API integration at scale
Production deployment and monitoring

Advanced Topics:

Multi-agent coordination and communication
Implementing reasoning patterns (ReAct, Chain-of-Thought)
Building feedback loops for self-improvement
Handling failures and edge cases gracefully
Cost optimization for agentic systems
Security and safety considerations

Why This Course Completes Your AI Education:

While other courses teach you individual skills, this one shows you how everything fits together. You’ll understand the architecture of production agentic AI systems, learn best practices from real deployments, and avoid common pitfalls.

The 2026 edition includes the latest developments in agentic AI, including MCP for standardized agent communication, advanced reasoning techniques, and patterns for building reliable autonomous systems.

You’ll Be Able To:

Architect complete agentic AI solutions
Build agents that reliably accomplish complex goals
Implement multi-agent collaboration patterns
Deploy and monitor production agent systems
Optimize for both performance and cost

Perfect If You’re:

An engineer building serious AI systems
Interested in the complete agentic AI stack
Wanting to stay ahead of AI trends
Ready to build the future of autonomous AI

Here is the link to join this course — The Complete Agentic AI Engineering (2026)

How to Choose the Right AI Course for You?

Here is a simple to the point guide to choose the right course for you:

Start with The AI Engineer Course 2026: Complete AI Engineer Bootcamp if you’re completely new to AI and need foundational knowledge.

Jump into “Prompt Engineering Bootcamp” if you’re already using AI tools and want to become a power user immediately.

Pick “LangChain Development” if you’re a developer ready to build your first AI application.

Choose “AutoGen AI Agents” if you want to work on cutting-edge multi-agent systems.

Go with “Complete Agentic AI Engineering” if you want comprehensive coverage of modern agentic AI.

My Recommended Learning Path for 2026

Here’s how I’d approach learning AI skills in 2026:

Month 1–2: Foundation

Start with AI A-Z to understand fundamentals
Practice with the Prompt Engineering Bootcamp daily
Build small projects to apply what you learn

Month 3–4: Application Development

Dive deep into LangChain
Build 3–5 real applications (chatbots, RAG systems, etc.)
Focus on production-ready code, not just prototypes

Month 5–6: Advanced Agentic AI

Learn AutoGen and multi-agent systems
Take the Complete Agentic AI Engineering course
Build a complex multi-agent project

Throughout: Keep Practicing

Build side projects regularly
Contribute to open-source AI projects
Stay updated with AI news and papers
Join AI communities and share your work

Why Udemy for AI Learning?

Udemy’s courses offer several advantages for learning AI skills:

Practical, hands-on approach — You build real projects, not just watch theory
Affordable pricing — Often available for $10–15 during sales
Lifetime access — Learn at your own pace, revisit whenever needed
Updated content — Courses are regularly updated with new techniques
Active communities — Q&A sections help when you’re stuck

The AI Skills Gap Is Your Opportunity

There’s a massive shortage of people who can actually build with AI.

Companies are desperately seeking engineers who understand prompt engineering, can develop with LangChain, and know how to architect agentic systems.

These aren’t “nice to have” skills anymore — they’re becoming baseline requirements for modern developers. The good news? You can learn them right now, and the investment will pay dividends throughout your career.

Final Thoughts

That’s all about the best Udemy courses to learn AI skills in 2026. AI is the most transformative technology of our generation, and 2026 is the perfect time to build your skills. The field is mature enough to have great learning resources but still early enough that learning now gives you a massive advantage.

Each of these five courses teaches skills that complement each other. Start with one, master it, then move to the next. Within six months of dedicated learning, you can go from AI beginner to building sophisticated agentic systems.

The question isn’t whether AI will impact your career — it’s whether you’ll be creating the AI future or just reacting to it.

Start your AI journey today. The best time to learn was yesterday. The second-best time is now.

By the way, if you want to join multiple courses on Udemy then you can also checkout Udemy’s Personal Plan, where you get access to best of Udemy’s 11000+ courses for a monthly fee of $30.

If you want to join multiple courses then Udemy Personal Plan is actually a better deal. You can also try for free for 7 days to get a feel of it.

So, what are you waiting for? Pick a course, start learning, and join the AI revolution!

Happy Learning!

Thanks for reading this article so far. If you find these Udemy Courses for learning essential AI skills like Prompt Engineering, LangChain, and Agentic AI then please share with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. — If you are a complete beginner on Agentic AI then I also recommend you to first go through a comprehensive course like The Complete Agentic AI Engineering (2026) Course, I highly recommend that to anyone who want to start with Agentic AI.

I Found Perfect Resources to Prepare for System Design Interview and They Are Awesome

2026-04-10T23:07:00.000-07:00

Hello guys, preparing for a technical interview in 2026 looks very different from what it did a few years ago.

With companies increasingly expecting engineers to demonstrate both coding proficiency and system design thinking, the tools you choose for your preparation can make or break your success.

Two names dominate the interview prep world — LeetCode and ByteByteGo.

LeetCode has been the go-to platform for coding problem practice for years, while ByteByteGo has emerged as a comprehensive, pattern-based learning ecosystem for mastering the why behind coding and design.

I found Leetcode for System Design, and it's Awesome

2026-04-09T08:04:00.000-07:00

credit- codemia.io

Hello Devs, if you're preparing for software engineering interviews, particularly MAANG, then you already know that Data Structures & Algorithms (DSA) and System Design are two key areas where you will be tested rigorously.

While LeetCode is the go-to platform for DSA, system design has always been a challenge.

While there are many websites and platforms to prepare for System Design Interviews like ByteByteGo, DesignGurus.io, Exponent, Educative, and Udemy, there is nothing like LeetCode.

These are great resources to learn fundamentals, go through case studies, and understand the theory part of the System design, but LeetCode-style practice is one thing that is missing - until now.

I recently found Codemia.io, and I must say, it feels like the LeetCode for System Design.

If you've struggled with structuring your system design answers, getting real feedback, or knowing whether your approach is correct, Codemia.io is a game-changer.

They not just have the biggest collection of System Design and OOP Design problems for practice, they also have a free System design course called Tackling System Design Interview Problems, which is a great free resource to learn essential System Design concepts.

It's a short course with 2 hours of content, but powerful and also has quizzes to test your skills. Here are all the key System design topics you can learn on this free course:

Now, let's check out how Codemia.io can help you to prepare better for your System design and OOP Design interview, and why I think it's like Leetcode for System design.

Most system design resources today are long, text-heavy articles or expensive courses. The problem?

No hands-on practice - Reading about system design isn't enough; you need to actively design solutions.
No structured progression --- Unlike DSA, where problems are categorized by difficulty, system design prep often feels random and overwhelming.
No evaluation or expert feedback --- You don't just need an answer; you need to know why one design is better than another.

This is where Codemia.io changes the game.

Instead of just giving you theory-heavy content, Codemia.io provides an interactive, structured, and guided approach to system design. Here's what I loved:

1. Real-World System Design Problems

Codemia.io has over 120+ system design problems, each with a structured approach similar to how LeetCode presents DSA problems.

For example, consider the classic "Design a URL Shortening Service" problem.

You start with:
1. Functional and Non-Functional Requirements
2. Capacity Estimation
3. Database Schema and API Design
4. High-Level & Low-Level Design

It guides you step by step so you don't feel lost.

Bonus: You also get access to a drawing board where you can sketch your architecture, just like in a real system design interview.

And most importantly, they also share expert solutions for most of the problems to see how an expert should answer that question. For example, here is the solution of how to design a URL shortening service, and it's also available for free

2. Difficulty-Based Categorization

Just like LeetCode, both System design and object-oriented design problems are categorized as:

Easy --- Foundational concepts like Load Balancing, Caching, Message Queues
Medium --- Scenarios like Rate Limiting, Search Autocomplete, Real-Time Chat Systems
Hard --- Complex designs like Distributed Databases, Cloud Storage, and Microservices Architecture

Each problem also includes company tags so you can focus on what's asked at FAANG and other top tech companies. For example, this how to design Twitter problem is a medium-scale problem, which you can see to get some experience. It's also free.

3. AI-Powered Hints & Evaluations

One of the best features is AI-assisted guidance. You get to chat with the coach --- the AI agent that will help you with the question and solution.

1. If you get stuck, AI provides hints --- just like LeetCode's hint system.

2. If you submit a design proposal, AI evaluates it against industry best practices.

3. You get automated feedback on scalability, fault tolerance, and efficiency.

This bridges the gap between self-learning and expert mentorship.

Beyond System Design: Object-Oriented Design & AI Interviews

Codemia.io goes beyond just system design. It also covers Object-Oriented Design (OOD) Questions. If you don't know, Object-Oriented Design is a common low-level design (LLD) round at FAANG.

Here are OOP problems you can solve on codemia.io to get some practice:

Classic problems like Parking Lot, ATM Machine, and Hotel Booking System
Step-by-step UML diagrams and class structure explanations
Comparison of different design patterns

If you struggle with OOD interviews, this is a goldmine.

Here is also all the OOP design problems available on Codemia.io

Now, let's see how codemia.io compares with other popular resources we have used in the past to prepare for System Design interview, notably DesignGurus.io, whose Grokking the System Design Interview course is also one of my favorites, and Educative.io, whose modern System design course is also a great resource.

You can see that codemia.io has the highest number of practice problems, 120+ and growing. No other platform has that many questions, which is also a big plus point of this platform, and that's why I called it "Leetcode of System Design".

The second important point is an expert-written solution, also known as an editorial solution on this website. There are more than 80+ such solutions, which are a great resource to compare your solution, learn from them, and also find how to answer such questions.

What point to mention, what should you discuss, tradeoffs, and so much more.

Another plus point of codemia.io is that it has object-oriented programming questions, which are not available in other courses, though DesignGurus.io has Grokking the Object Oriented Design Interview course, which you can use for OOP design practice, but again, when it comes to numbers, codemia.io wins.

So far, we have compared the content, but if we talk about the platform, codemia.io has been especially designed for online practice, particularly for design questions.

It comes with Interactive learning tools, interactive feedback and evaluation, a chatbot, and a great design tool for drawing. No other platform supports so many features that are essential to master system design.

Then there is community, and you can also see the solutions of other folks to learn from them. I love this feature as it allows me to see what other folks are thinking and how they solve that problem. This comparative analysis has helped me a lot to learn key system design concepts.

Overall, I think codemia.io is a great platform to prepare for System design and OOP design interviews. You may find courses, but it's hard to find a platform like this.

I highly recommend it for anyone preparing for System Design and Tech interviews. And, if you want to join now, you can also use the discount code PROMOTION20 to get 20% off now.

Here is the link - 20% OFf on Codemia.io

Final words

If you're preparing for FAANG system design interviews, Codemia.io is a must-try. It solves the biggest problems in system design prep:

Structured learning path (instead of random articles)
Real-world hands-on practice (instead of just reading)
Expert evaluation & AI feedback (so you know what to improve)
Mock interviews to simulate real conditions

I'm still exploring Codemia.io, but what I've seen so far is truly impressive.

If you've tried it, let me know what you liked or didn't like.

Thanks for reading this article so far. If you like this article, then please share it with your friends and colleagues. If you have any questions, feel free to ask in the comments.

P. S. - They are also offering 20% discount now, and you can get access for just $59 for one year, the original price is $120 so you have a chance to save $60 and also learn System design better.

I Tried 20+ Azure Developer Associate Certification Courses and Practice Tests: Here Are My Top 5 Recommendations

2026-04-08T06:03:00.000-07:00

Hello guys, in this AI age of Software Development, Cloud computing has become an essential skill for developers, and Microsoft Azure is one of the leading cloud platforms today.

If you’re a developer looking to build, deploy, and manage applications on Azure, getting the Microsoft Certified: Azure Developer Associate (AZ-204) certification is the best way to showcase your skills in 2026.

As an instructor, I highly recommend this certification because it validates your expertise in developing cloud applications and services on Azure.

It covers essential skills like Azure Functions, API Management, Cosmos DB, Azure Storage, and DevOps tools like Azure DevOps and GitHub Actions.

Since many companies are now moving their applications to Azure, increasing the demand for certified Azure developers.

Whether you are a backend developer, a cloud engineer, or a DevOps professional, the Azure Developer Associate certification will help you stand out in the job market.

To pass the AZ-204 exam, you need strong theoretical knowledge and hands-on experience with Azure. The best way to prepare is through online courses that offer both structured learning and practical labs.

Earlier, I have shared the best AZ 900 courses and today, I am going to share the best AZ 204 online courses and practice tests for the Azure Developer associate exam.

Udemy has some of the best courses to prepare for AZ-204, and I have selected the top five that will help you pass the exam on your first attempt.

By the way, if you are new to Azure then you can also start with this comprehensive course Microsoft Azure: From Zero to Hero — — The Complete Guide by solution architect Memi Levi. It’s a great resource to design and build modern cloud apps from a certified Azure Architect

5 Best Udemy Courses to Crack AZ-204 Exam in 2026 with Practice Tests

Without any further ado, here are the best Udemy courses you can join to prepare for AZ-204 certification exam and become a certified Azure developer. I have included both theory courses as well as practice test which you can take to asses your preparation level before real exam.

1. AZ-204 Developing Solutions for Microsoft Azure— JAN 2026

This is one of the best courses to prepare for the AZ-204 certification. It provides a comprehensive and practical approach to learning Azure development.

What you’ll learn:

Developing Azure Functions and API Management
Implementing Azure Storage solutions (Blob, Table, Queue, Cosmos DB)
Deploying applications on Azure App Services and Kubernetes
Monitoring and troubleshooting applications on Azure
Integrating security and authentication with Azure AD and Managed Identities

This course is fully up-to-date for the latest AZ-204 exam syllabus and includes hands-on labs to help you gain real-world experience.

Join here: AZ-204 Developing Solutions for Microsoft Azure — JAN 2026

2. Developing Solutions for Microsoft Azure (AZ-204)— Exam Guide

This course is great for exam preparation and includes detailed explanations of key concepts along with exam-focused content.

Key highlights:

Step-by-step walkthrough of AZ-204 exam topics
Real-world Azure development scenarios
Security, identity management, and authentication
Azure DevOps, CI/CD pipelines, and GitHub Actions
Azure Messaging Services — Event Grid, Service Bus, and Queue Storage

If you are looking for a structured and well-organized exam guide, this is a fantastic choice.

Join here: Developing Solutions for Microsoft Azure (AZ-204) — — Exam Guide

3. AZ-204 Microsoft Azure Developer Practice Tests

If you want to test your knowledge before the real exam, practice tests are essential. This Udemy course provides six full-length practice exams that simulate the real AZ-204 exam.

Why this course is useful:

5 Timed exams to improve speed and accuracy
175+ practice questions covering all AZ-204 domains
Detailed explanations for every question
Helps you identify weak areas for revision

Many students fail the first attempt because they don’t practice enough questions. These mock tests will ensure you are fully prepared for the exam.

Join here: AZ-204 Microsoft Azure Developer Practice Tests

4. Azure Crash Course — The basics with Hands-On in 3 hours!

If you’re short on time and need a quick refresher before the exam, this crash course is a great option. It provides concise explanations of all the important topics in less time.

What you’ll get:

Quick review of Azure services needed for AZ-204
Best practices for developing applications on Azure
Security and authentication concepts in a nutshell
Exam tips and tricks

This course is best for those who already have some Azure experience and just need last-minute revision before the exam.

Join here: Azure Crash Course — The basics with Hands-On in 3 hours!

5. Hands-On Azure Labs: Applying Practical Real-World Skills

This course is focused on real-world application development using Azure. If you want more than just certification and need to apply your Azure knowledge to real projects, this course is perfect.

While this course is created for AZ-104 and AZ-305 exam the 29 interconnected hands on Azure Lab Simulations will teach you how to build a complete cloud solution

Key topics covered:

Building serverless applications using Azure Functions
Developing microservices and deploying with Kubernetes
Implementing API Management and securing APIs
Working with Azure Storage and Cosmos DB
Deploying applications using CI/CD pipelines

If you want hands-on experience with Azure beyond just exam preparation, this course is highly recommended.

Join here: Hands-On Azure Labs: Applying Practical Real-World Skills

Conclusion

That’s all about the best Udemy courses to crack AZ-204 Exam in 2026. If you want to pass the Azure Developer Associate (AZ-204) exam, I highly recommend starting with Microsoft Azure Developer Associate (AZ-204) — — Hands-On Course.

This course covers everything you need for the exam and provides real-world experience with Azure services.

Good luck on your Azure certification journey!

Other Microsoft Azure and Cloud certifications you may like to explore

Thanks for reading this article so far. If you find these Microsoft Azure Administrator courses, AZ-104 useful, then, please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. —If you are new to Microsoft Azure then I also suggest you to go through Microsoft Azure: From Zero to Hero — — The Complete Guide by solution architect Memi Levi. It’s one of the best online course to learn Azure in depth. If you need more choices, you can also see this article.

11 Best Microsoft Azure Courses for Beginners and Experienced Developers in 2026

A collection of best online courses to learn Microsoft Azure Cloud Platform and Azure DevOps in depth

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Is 101 Blockchains Academy’s Subscription Really Worth It in 2026? Review

2026-04-06T21:52:00.000-07:00

Hello guys, the blockchain and Web3 space has evolved rapidly over the past few years. With new roles emerging in AI, FinTech, Web3, and enterprise blockchain, professionals are constantly looking for reliable platforms that offer structured, career-focused learning.

Among the many platforms out there, 101 Blockchains Academy has positioned itself as one of the top destinations for professionals aiming to gain credibility through certifications and industry-recognized credentials.

The best thing is that they are offering 50% discount on their premium plan but with its Premium Plan priced at $900 many learners wonder — is it really worth it?

Let’s take a closer look.

1. What Is the 101 Blockchains Premium Plan?

The Premium Plan is the top-tier membership that provides unlimited access to every course, certification, and career path available on the platform.

It’s designed for professionals who want a complete blockchain, Web3, and AI learning package, including:

Unlimited access to 60+ professional courses
All AI and Blockchain certifications
Skill and Career Paths for guided learning
On-demand sessions and live events
Exclusive community membership and council access
CV and interview preparation support

The plan also includes members-only live research sessions and exclusive event invitations, which add real professional networking value that most competitors don’t offer.

Here is the link to learn more about it — Explore Blockchains 101 Premium Plan

2. How Does It Compare to Other 101 Blockchains Plans?

Now, let’s compare all the subscription plans and options 101 Blockchains provides you

1. Standard Plan — $300

Provides access to a limited selection of courses and certifications.
Ideal for beginners exploring blockchain or those who want to test the platform before committing to higher tiers.

2. Career Paths Plan — Starts at $159

Offers structured learning paths tailored for specific job roles in blockchain, Web3, and AI.
Best suited for career-focused learners who want a guided roadmap toward a particular professional goal.

3. Skill Paths Plan — Starts at $149

Focuses on targeted skill development in areas like DeFi, NFTs, the Metaverse, and more.
A great choice for upskilling professionals looking to enhance specific competencies rather than complete programs.

4. Premium Plan — $900

Grants unlimited access to all certifications, courses, and learning paths.
Designed for advanced learners and career changers who want a comprehensive, all-in-one membership for long-term learning.

If you plan to pursue multiple certifications or switch careers into blockchain or AI, the Premium Plan can actually save you money over time.

For example, individual certifications like the Certified Fintech Expert (CFTE) or Certified Blockchain Security Expert (CBSE) cost around $399 each — meaning the Premium Plan pays for itself after just two or three certifications.

3. What Certifications Are Included?

The Premium Plan unlocks access to all professional certifications offered by 101 Blockchains. These include both blockchain fundamentals and advanced AI-driven topics such as:

These certifications are recognized by top blockchain organizations and consulting firms, and the academy provides career-oriented learning paths that align directly with industry roles.

4. Strengths of the Premium Plan

✅ All-access membership:
You get unrestricted access to all learning materials, including blockchain, Web3, AI, and FinTech.

✅ Career-focused guidance:
Career paths, interview preparation, and CV support make it ideal for professionals transitioning into tech roles.

✅ Industry credibility:
Certifications like CEBP and CAIP are widely recognized, adding professional weight to your LinkedIn or CV.

✅ Community and networking:
The Premium membership opens up members-only live sessions, events, and council memberships — creating networking opportunities in a fast-growing industry.

✅ Continuous updates:
Courses are regularly updated to reflect the latest blockchain and AI trends, ensuring your skills stay relevant.

5. Weaknesses and Limitations

❌ High upfront cost:
At $900, it’s a serious investment. For learners who only want one or two certifications, individual purchases may be more cost-effective.

❌ Self-paced only:
While content is rich, the lack of instructor feedback or 1-on-1 mentorship can be a drawback for some learners.

❌ Specialized focus:
If your interests lie outside blockchain, Web3, or AI, the platform may not provide enough variety compared to Coursera or Udemy.

6. Verdict — Is the Premium Plan Worth It?

If you’re committed to building a career in blockchain, Web3, AI, or FinTech, the Premium Plan from 101 Blockchains is absolutely worth it.

It’s not just about the number of courses — it’s about structured learning, recognized certifications, and career guidance.

However, if you’re still exploring the field, the Standard Plan ($300) or Career Path bundles might be a better starting point before upgrading.

The great thing is that they are offering a huge discount on premium plan, up to 50% OFF which means you can get it for just $75 per month instead of $150 per month. I think this is the best time to join 101 Blockchains Academy and start your career in AI and Blockchains.

Here is the link to join — Join 101 Blockchains Plan for 50% OFF

Final Thoughts

That’s all in this review of 101 Blockchains Premium plan and whether its worth it or not. In a landscape full of generalist platforms, 101 Blockchains Academy stands out for its depth, credibility, and career relevance.

The Premium Plan is best suited for professionals serious about advancing in blockchain, Web3, and AI — and who want a one-time investment for long-term learning.

You can check the 101 Blockchains Premium Plan here and see if it fits your professional goals.

Other Blockchain and Technology articles you may like

Thanks for reading this article so far. If you like this article then please share with your friends and colleagues if you find them useful. If you have any questions or feedback, then please drop a note.

P. S. — If you are serious about learning Blockchain technologies and looking for the best Blockchain certification to start with then this Enterprise Blockchain Certification by 101 Blockchain is the best resource to start with. Many of my students and readers have taken this course and feedback has been awesome.

Review — Is Certified Enterprise Blockchain Professional Certification (CEBP) worth it?

Do you want to become a Blockchain professional and wondering whether to join 101 Blockchains CEBP — Certified…

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I Tried 50+ Software Development Courses on Educative: Here Are My Top 10 Recommendations

2026-04-06T06:58:00.000-07:00

image_credit — Educative.io

Today, I am going to share with you a relatively new online learning platform called Educative, a text-based, interactive learning platform. If you are an online learner like me, you might have heard about Educative or come across some of its excellent and most popular courses like Grokking the System Design Interview course, which I have mentioned earlier in my article about System design Interviews questions.

So, what is so special about Educative? How different is it from other popular online platforms like Udemy, Coursera, Pluralsight, and CodeCademy? Well, Educative is different because it is mainly a text-based learning platform that allows you to code and program right in the browser.

Unlike Udemy or Coursera, where you learn by watching videos, you learn more by reading and trying code samples in Educative.

There are some distinct advantages of learning by reading, particularly rich-text. For example, reading is always faster than watching videos, and I have seen many people just skipping to find out interesting information between long and boring videos.

With text, you can skip faster and also take notes easier. The Educative’s cutting-edge technology also allows you to run code in the browser. This means you can learn Python, Java, Ruby, JavaScript, and even C++ in the browser using Educative’s innovating code widgets.

In short, the Educative platform has a lot to offer as a platform and it’s worth looking at, but just the platform will not be enough unless you have some excellent courses that utilize the full potential of the platform and provide you an amazing learning experience and educative is full of them.

In this article, I am going to share with you the top 11 Educative Courses for Programmers and Software Engineers. You can check out these courses to level up essential skills for programmers like System design, Algorithms, Docker, Kubernetes, React, JavaScript, C++, and Dynamic programming. These are the truly useful skills to master and Educative’s interactive learning platform will help you to master them quickly.

Grokking the System Design Interview - Learn Interactively

System design questions have become a standard part of the software engineering interview process. Performance in these…

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My Favorite Educative Courses for Coding Interviews and Software Development in 2026

Without wasting any more of your time, here is a list of the best interactive, text-based courses from Educative for programmers and software engineers.

These interactive text-based courses have been created by experts and Educative’s state-of-the-art platform that makes learning easy with interactive quizzes, and the ability to run the program right from your browser.

1. Grokking the System Design Interview

This is actually the first and probably the best course I have seen on Educative. Created by Design Guru this course tackles the topic of System design.

If you have attended coding interviews then you may know that dealing with System design questions is not easy, especially if you don’t have much experience in real-world software development.

Things like caching, scalability, fault-tolerance, Microservices, database design are essential to design software but not easy to master.

This course provides an excellent introduction to all the things you can keep in mind while designing a new system like a website, an application, or just an app.

This interactive course is a must if you want to crack the coding interview but even if you are not preparing for an interview, you will learn a lot about software architect and design by going through this course which will eventually make you a better programmer.

Here is the link to join this course — Grokking the System Design Interview

2. Grokking the Coding Interview: Patterns for Coding Questions

This one is another fantastic course from the Educative platform for programmers. Unlike other online courses where you prepare for coding interviews by solving problems, this course will teach you how to find underlying coding patterns so that you can solve similar problems on coding interviews.

This technique of finding patterns and developing coding sense is a must if you want to crack a coding interview on companies like Google, Microsoft, Amazon, Apple, Facebook, NetFlix, or any FAANG companies.

Why? because they often give you a coding problem that you have never seen before. If you know how to break the problem into recognized patterns you can solve them.

I highly recommend this course to anyone who is preparing for coding interviews but just like the previous course, even if you are not preparing for an interview, you can join this course to improving your coding skill and become a better developer.

Here is the link to join this coding course — Grokking the Coding Interview Patterns

3. Grokking Dynamic Programming Patterns for Coding Interviews

This is the third course I have chosen from Educative for programmers preparing for coding interview and that’s because Educative really have the best collection of coding interview courses. This course tackles another difficult topic of Dynamic Programming from coding interviews.

If you don’t know Dynamic Programming is a technique to solve complex problems by breaking them down into smaller similar problems. It uses Recursion and Memoization to solve individual parts to eventually solve the bigger problem, but it’s not easy to master.

This course will give you all the knowledge you need to master Dynamic Programming and you will learn by solving the most popular dynamic programming problem from interviews so that you are ready to solve them when you really need them.

Here is the link to join this course —Grokking Dynamic Programming Patterns for Coding Interviews

4. Docker for Developers

If there is one tool every programmer should learn this year, then it should be Docker. If you don’t know what is Docker? then let me tell you that Docker is a container tool that solves the problem of executing a complex application with so many dependencies.

It also solves the problem of deployment on the scale because it bundles the application and all its dependency into a single Docker image (similar to a tar file) and you just have to deploy that image instead of setting up the whole environment by installing OS, shells, and different dependencies.

The best thing about Docker is that Docker containers are very lightweight and can be deployed on any physical and virtual machines, which makes them ideal for cloud deployments like AWS, GCP, and Azure.

This course, Docker for Developers will teach you all the things a Developer should know about Docker, and Educative’s interactive learning platform means you will learn Docker by practicing and doing hands-on exercise

Here is the link to join this interactive course — Docker for Developers

5. A Practical Guide to Kubernetes

Along with Docker, Kubernetes is another tool that is taking the world by storm. It takes the container deployment to the next level.

While Docker solves the problem of application deployment by bundling application code, dependency, and runtime environments like OS and Java, .NET, and Node into a single Docker image file, it is still not easy to spawn and manage hundreds and thousands of container depending upon scalability needs.

Kubernetes solves this problem by automating container management. It can automatically create new containers when your traffic doubles up and can shut them down when your application load returns to normal.

If you aspire to become a DevOps engineer or just want to become a full-stack developer, learning Kubernetes can enhance your profile and this course can really help you to learn Kubernetes in depth.

Here is the link to join this Kubernetes course — A Practical Guide to Kubernetes

6. The Good Parts of AWS: Cutting Through the Clutter

AWS is another skill that I think every developer should acquire, not just to enhance their profile and CV but also to learn how the application will be executed in the near future.

Since cloud computing is the future of software development and more and more applications are now run from the Cloud, it becomes imperative for a developer to know how the cloud works and how essential things like computers, memory, storage, and network are provisioned.

but, learning AWS can be tedious and time-consuming with so many services and their options, that’s where this course help. This course teaches you the good and essential parts of AWS.

You won’t find most of the knowledge shared in this course anywhere else or in the AWS docs. The goal here is to help you realize which AWS features you should be using — features that have passed the test of time by being at the backbone of most things on the Internet.

Here is the link to join this AWS course — The Good Parts of AWS

7. The Complete Guide to Modern JavaScript

There is no doubt that JavaScript is the kind of web development, the most lucrative path of Software development but JavaScript has changed a lot in the last few years. It’s not the same JavaScript you and I learned as part of our client-side validation 10 years ago.

Modern JavaScript is a much more powerful programming language including both OOP and Functional programming features to write clean and concise code. This course, The Complete Guide to Modern JavaScript will guide you from the basics of the language to all the new features introduced up until now.

Whether you are a beginner to JavaScript or already have some experience, this course will only enhance your JavaScript knowledge and make you a better developer.

You’ll also test your knowledge with quizzes and some coding challenges by using the Educative’s interactive online learning platform.

Here is the link to join this awesome course — The Complete Guide to Modern JavaScript

8. C++17 in Detail: A Deep Dive

Apart from coding interview courses, C++ is another topic where Educative have the best courses. They have courses covering individual C++ areas like Template, Embedded programming, and then courses like this one which goes deep on C++17.

This course describes all the significant changes in C++17 and will give you the essential knowledge to stay at the edge of the latest features. What’s more, each section contains lots of practical examples and uses a bottom-up approach to give you a more comfortable start

If you want to take your C++ skills to the next level then I highly recommend this course to you and if you want, you can also check out their other C++ titles.

You know what, you can actually take an Educative subscription to try out all these courses instead of buying them individually. It’s a much better deal because with the cost of $18 per month you get access to their 140+ course library.

Here is the link to join this C++ course — C++17 in Detail: A Deep Dive

9. Java Multithreading for Senior Engineering Interviews

As I said, Educative have the best online courses for preparing for programming job interviews, and concurrency is one of the key skills for coding interviews. It’s not just important to pass the interview but also to work on today’s high-performance and highly concurrent applications.

Concurrency in Java is one of the most complex and advanced topics brought up during senior engineering interviews. Knowledge of Concurrency and Multithreading can put interviewees at a considerable advantage.

This course lays the foundations of advanced concurrency and multithreading and explains concepts such as Monitors and Deferred Callbacks in depth. It will also teach you how to solve popular concurrency coding problems that can be asked about in interviews like the Reader-Writer Problem and the Dining Philosopher Problem.

Whether you are a beginner or an experienced Java programmer, I highly recommend this course to you if you want to take your concurrency skills to the next level

Here is the link to join this thread course — Java Multithreading for Senior Engineering Interviews

10. The Road to React: The One with Hooks

There is no doubt that React.js is the number one framework for frontend development. Just like JavaScript is a kind of Web development and Python is the king of Data Science, React is also the most important for any frontend developer.

You may know to React already but the thing is that React.js keeps changing and introduced a new feature in every release and it’s not easy to keep up with them and that’s where this course help.

In this course you will take a deep dive into React fundamentals, covering all new React concepts including Hooks. I do address some legacy features in case you’re working with an older codebase, but the majority of this course will focus on working with modern React.

You will learn how to style your app, techniques for maintaining your app, and some more advanced concepts like performance optimization.

Here is the link to join this React course — The Road to React: The One with Hooks

11. Web Application and Software Architecture 101

Software architecture is one topic that many developers don’t pay the required attention to. Unfortunately, there are also not good materials available to learn about different software architecture, their pros and cons together.

You need to search hard and need to know how to find those gem of articles and you may find them if you are really lucky but for most of us it just passes by and so this useful topic remains weak. This course solves that problem by explaining everything about Software architecture programmers need to know.

If you’re looking for a complete course on web application and software architecture, I recommend checking out this Web Application and Software Architecture 101 course on Educative. This is a useful course for anyone looking to strengthen their overall knowledge of software architecture.

Here is the link to join this awesome course — . Web Application and Software Architecture 101

That’s all about the 11 best Educative Courses for Programmers and Software Engineers. This list includes courses that are very good for preparing programming interviews like Grokking series as well as some awesome courses to learn tools like Docker and Kubernetes and programming languages like Python, Java, C++, and JavaScript.

If you find these online courses and Educative platforms useful then you can also consider getting an Educative Subscription which gives you access to their 100+ courses for just $14.99 USD per month.

Sometimes you need this flexibility of joining a course you want instead of purchasing it. It’s also a better deal if you are going to attend more than a couple of courses on Educative in a year.

Other Useful Resources for Programmers and Developers

Thanks for reading this article so far. If you find these online courses and Educative platforms useful then please share with your friends and colleagues. If you have any questions or feedback then please drop a note. Learning has never been so easy and fun.

P. S. — If you are looking for some free courses to explore the Educative platform and their interactive learning tools then I also suggest you check out my earlier article about 10 Free Educative courses for Programmers and Developers. There I have mentioned free Educative.io courses for programmers to learn Java, Python, C++, JavaScript, and Web development.

Learn Python 3 from Scratch - Free Interactive Course

Learn Python 3 for free with this interactive course, and get a handle on the most popular programming language in the…

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I Tried 100+ AI Courses on Udemy: Here Are My Top 5 Recommendations for AI Engineers

2026-04-04T23:41:00.000-07:00

Hello guys, AI is hot now, I mean really hot. While tech jobs are declining and its not easy to get a job in Tech as it was before, the AI related jobs are flooding the market.

Just search for AI Engineer jobs on LinkedIn and you will find it all kinds of companies are looking for AI Engineers.

and why not? Artificial Intelligence (AI) is transforming industries at an unprecedented pace, making AI engineering one of the most sought-after career paths.

From natural language processing (NLP) to machine learning (ML) and large language models (LLMs), AI engineers play a crucial role in developing intelligent applications, automating tasks, and improving decision-making across various domains.

If you’re looking to break into AI engineering or advance your skills, and looking for resources to star with then you have come to the right place.

In the past, I have sharedbest AI courses, best ChatGPT courses, AI Engineer RoadMap, and best courses to learn deep learning and today, I am going to share best online courses from Udemy to become an AI Engineer in 2026.

When it comes to learning new skills, Udemy is one of the best place. It not only is most affordable but also offers several high-quality courses that provide hands-on training, real-world projects, and industry-relevant knowledge.

In this article, we’ll explore the top five Udemy courses to become an AI engineer in 2026, by the way, if you just need one course to start with then I suggest you to join The AI Engineer Course 2026: Complete AI Engineer Bootcamp course on Udemy. It’s one of the most complete course to become an AI Engineer/Developer in 2026.

Why become an AI Engineer in 2026?

AI engineering is one of the fastest-growing career fields, with an increasing demand for professionals skilled in machine learning, deep learning, and AI development.

Here are some key reasons why pursuing AI engineering is a great choice in 2026:

High Salary Potential: AI engineers earn some of the highest salaries in the tech industry, with median salaries ranging from $120,000 to $200,000 per year, depending on experience and location.
In fact, if you spend time, you can also become Principle AI Engineer which is a senior level job on many banks and other companies and offer handsome package.
Strong Job Market: AI adoption is expanding across industries like healthcare, finance, retail, and cybersecurity, increasing the demand for AI professionals.
Diverse Career Paths: AI engineers can work in various domains, including natural language processing, computer vision, reinforcement learning, and AI ethics.
Impactful Work: AI engineers contribute to solving real-world problems, from medical diagnostics to self-driving cars and personalized recommendations.

Now, let’s dive into the best Udemy courses to help you build the skills necessary to become a proficient AI engineer in 2026.

By the way, its expected from AI Engineer to know Python and if you don’t know Python its better to first learn Python before jumping into AI and ML related skills.

If you need a resource, I highly recommend you to start with 100 Days of Code: The Complete Python Pro Bootcamp by Angela Yu.

Based upon #100DaysOfCode missing this is also one of the most popular Python course on Udemy with more than 1.5 million students. I highly recommend this to anyone starting with Python in 2026.

5 Best Udemy Courses to become an AI Engineer or Developer in 2026

Without any further ado, here are the Udemy courses you can join to become an AI Engineer in 2026. These courses are carefully chosen to give you broader knowledge about different fields like foundation, Machine Learning, Deep Learning, Advanced AI, Tools and Frameworks like NumPy, TensorFlow, Pandas, Hugging Face etc.

1. The AI Engineer Course 2026: Complete AI Engineer Bootcamp

This comprehensive course is one of the best choices for anyone looking to become an AI engineer. Covering everything from Python programming to advanced deep learning and large language models (LLMs), this bootcamp provides a structured approach to mastering AI technologies.

Here are things you will learn in this course.

Python programming for AI development
Fundamentals of natural language processing (NLP) and transformers
Implementing large language models (LLMs) using Hugging Face and LangChain
API integration for AI-driven applications
Practical AI engineering projects and real-world case studies

Instructor: 365 Careers

Level: Beginner to Advanced

Why Take This Course?

Covers all essential AI engineering topics in a structured manner

2. Hands-on projects for real-world AI applications

3. Includes training on cutting-edge AI tools like Hugging Face and LangChain

Here is the link to join this course —The AI Engineer Course 2026: Complete AI Engineer Bootcamp

2. Deep Learning A-Z: Hands-On Artificial Neural Networks

Deep learning is at the core of AI engineering, and this course provides a hands-on approach to building deep neural networks.

In this course, you’ll learn about artificial neural networks (ANNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs) using Python and TensorFlow.

Instructor: Kirill Eremenko, Hadelin de Ponteves

Level: Beginner to Intermediate

What You Will Learn:

Building deep learning models from scratch
Understanding and implementing CNNs, RNNs, and LSTMs
Real-world applications in image recognition and NLP
Hyperparameter tuning and model optimization

Why Take This Course?

✅ Great introduction to deep learning for AI engineers

✅ Includes practical examples and real-world applications

✅ Covers advanced topics like generative adversarial networks (GANs)

Here is the link to join this course — — Deep Learning A-Z: Hands-On Artificial Neural Networks

3. Machine Learning A-Z: AI, Python & R for Data Science

This is one of Udemy’s most popular AI courses, covering the fundamentals of machine learning and artificial intelligence. It is ideal for beginners who want to understand AI algorithms and implement them using Python and R.

Instructor: Kirill Eremenko, Hadelin de Ponteves

Level: Beginner to Intermediate

What You will Learn:

Supervised and unsupervised learning techniques
Building ML models using Python and R
Real-world applications in finance, healthcare, and business analytics
Feature engineering, data preprocessing, and model evaluation

Why Take This Course?

✅ Covers both Python and R implementations

✅ Hands-on projects to build a strong portfolio

✅ Excellent for beginners in AI and machine learning

Here is the link to join this course — Machine Learning A-Z: AI, Python & R for Data Science

4. NLP —Natural Language Processing with Python

Natural Language Processing (NLP) is a crucial field in AI, powering chatbots, voice assistants, and text analytics. This course focuses on using Python and machine learning techniques to build NLP applications.

Instructor: Jose Portilla

Level: Intermediate

What You Will Learn:

Text preprocessing and feature extraction
Sentiment analysis and topic modeling
Building chatbots and AI-powered text applications
Deep learning methods for NLP, including transformers

Why take this course?

✅ Practical implementation of NLP techniques

✅ Covers both classical machine learning and deep learning approaches

✅ Helps build AI applications like chatbots and virtual assistants

Here is the link to join this course — — NLP —Natural Language Processing with Python

5. LLM Engineering: Master AI, Large Language Models & Agents

If you’re new to AI and want to understand how AI and Large Language Model or LLM works at a conceptual level, this course on Udemy is a must-take.

It is designed for beginners who want to explore AI’s applications and impact and want to learn foundational AI knowledge and key concepts.

Instructor: Ed Donner and Ligency Team

Level: Beginner

What You Will Learn:

The fundamentals of AI, deep learning, and ML
How AI is transforming industries
Key AI concepts like supervised vs. unsupervised learning
Ethical considerations and the future of AI

Why take this course?

✅ Ideal for beginners looking to understand AI basics\

✅ Taught by one of the leading AI researchers

✅ Helps you decide how to apply AI in your career

Here is the link to join this course — — LLM Engineering: Master AI, Large Language Models & Agents

2026 AI Engineer RoadMap

Here is also a nice AI Engineer RoadMap for 2026 where you will find all the skills you need to become a true AI Engineer companies are looking for. It contains:

Foundation (Mathematics and Programming)
Machine Learning Basics
Deep Learning
Advanced AI Concepts
Tools & Frameworks
MLOps etc

While it can take up to 2 to 3 years if you were to master all these technology, I think you should be able to apply for jobs with few months of learning and then continue your learning in parallel.

Conclusion

That’s all about 5 best Udemy Courses to become an AI Engineer or Developer in 2026. As I have said, becoming an AI engineer in 2026 is a rewarding career move, with immense opportunities in industries ranging from healthcare to finance, robotics, and beyond.

Udemy offers a variety of high-quality courses to help you gain AI skills, from beginner-friendly introductions to advanced machine learning and deep learning training.

If you’re serious about becoming an AI engineer, The AI Engineer Course 2026 is the best choice, covering LLMs, transformers, and API integration. For those interested in deep learning, “Deep Learning A-Z” provides a hands-on approach.

No matter where you are in your AI journey, these courses will equip you with the skills needed to succeed in one of the most exciting fields in tech.

By the way, if you want to join multiple course on Udemy, its may be worth getting a Udemy Personal Plan, which will give instant access of more than 11,000 top quality Udemy courses for just $30 a month. If you got a lot of time and want to save money, Udemy Personal Plan will be perfect for you.

Other Machine Learning and AI Resources for Programmers

P. S. — — If you are serious about moving into AI and Machine Learning field, I also suggest you learn Python, one of the most valuable skills when it comes to Machine Learning and AI. If you need resources, check out this list of the best Python courses to kick-start your journey.

10 Best Udemy Courses to Learn AI, ChatGPT and Machine Learning in 2026

The ultimate guide to mastering AI with Udemy’s top-rated courses

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I Tried 50+ Datacamp Courses: Here Are My Top 10 Recommendations for 2026

2026-04-04T02:40:00.000-07:00

Hello guys, if you are looking for the best and free Datacamp courses to learn Python and SQL and become a Data Scientist in 2026, then you have come to the right place. In the past, I have shared the best udemy courses to learn Python and the best courses for data science.

In this article, I will share both free and best Datacamp courses for Python developers and Data Science learners. Yes, you read it write, Datacamp also offers free courses and they are quality courses which you can take to learn at the skill on your own.

If you don’t know, Datacamp is a great platform to learn Data skills, and it has the best courses to learn Data skills like SQL, Data Science, and Python. They also have data certifications which can be used to learn key skills like Data Analysis and Data Engineering.

They are like CodeCademy for Data skills. They have interactive lessons, quizzes, video lectures, and creative exercises to teach key data skills, and that’s why it’s one of the best places to learn Python and SQL for data science.

Data science is a big field where the student needs to have many programming languages like python language and R.

Also, he needs to learn math and statistics, and they are mandatory to be a data scientist and maybe need to learn machine learning and deep learning to make predictions and all of these skills can be learned from one place called DataCamp.

Data nowadays is the core that keeps companies running and makes decisions based on the analysis of these data. This is the role of a data scientist. The DataCamp platform helps companies and individuals deal and work with data using many different tools and apply machine learning algorithms to these data.

8 Free Datacamp Courses to Learn Python, SQL, R, and Data Science in 2026

Here is my list of best Datacamp courses people can take to learn essential tech skills like Python and SQL and become Data scientists in 2026. There is a lot of demand for Data Scientists and Backend engineers with Python and SQL, and these Datacamp courses will teach you those from scratch.

From my 20 years of experience in tech, I can say that learning Python and SQL is the best decision of your life; unlike many frameworks and programming languages, Python and SQL have been around for more than 25 years, and there is still a great demand for them. Learning them is a good investment for life.

1. Introduction to Python [Free Course]

Python programming language is the language of the future since it is used in too many different industries like web development with Flask and Django frameworks also in data visualization with matplotlib library.

It also covers artificial intelligence using Tensorflow and Pytorch frameworks and Datacamp has created a course for learning this language from the beginning by understanding first the basics of this language like variables and data types, python lists, then moving to functions and importing packages, and finally, working with arrays using NumPy.

The best thing about this Datacamp course is that it's free, all chapters are free and you can access them by creating a free account.

Here is the link to join this free Python course — Introduction to Python

2. Introduction to SQL [Free Course]

If you are looking to be a database administrator or a data scientist, or even a web developer, then you need to learn the SQL language, which is the language that is used to communicate with the database and extract and filter the data to use it.

Datacamp has created an entire course teaching you the structure of the database and how to perform simple SQL queries, learn how to use comparison operators, use the aggregator functions, and finally, sort and group your results.

This is also one of the best free courses from Datacamp and if you are looking for free resources to learn SQL then you should check out this highly engaging SQL course on Datacamp.

Here is the link to join this course — . Introduction to SQL

3. Introduction to R [Free Course]

This is another free course from Datacamp to learn the R programming language for beginners.

Data scientists need to learn maths and statistics to work with data and perform analysis, so alongside learning python, they also need to learn the R language, which is considered easy to learn like python but used a lot in the statistics field and analysis and data visualization.

DataCamp offers a course in the R language, starting by learning the basics like arithmetic and variables and vectors, then learning metrics and performing computation with them, and more.

Here is the link to join this course — Introduction to R

4. Introduction to Tableau [Free Datacamp Course]

Tableau is a widely used software among companies such as Amazon to analyze their data, get insight for decision-making, and share the workbook between the team inside the company. You will learn first to import your data inside the software and its interface.

You will start the visualization process and customize them like slicing and dicing your data with filters. You will also explore how to visualize geographical data.

Finally, learn best practices to tell the story about your data and share your insight.

Here is the link to join this course for FREE — Introduction to Tableau

5. Data Analysis in Excel [Free Course]

Excel spreadsheet is a software developed by Microsoft.M. M. Most people think they are just used to store data and apply some easy functions. Companies are using this software to analyze big data and more.

You will start learning about the data analysis process and exploring the Excel interface. You will learn to sort the tables and nesting functions and learn about cleaning your data using a variety of functions and apply all of what you’ve learned to a real dataset.

Here is the link to join this course for FREE — Data Analysis in Excel

6. Introduction to Power BI [Free]

Another alternative for Tableau software that companies use is Power BI, which Microsoft developed and owned and can give you excellent visual analytics capabilities.

You will first discover the interface, start loading your dataset, and build a data model to understand the relationship between your tables and create some graphs.

Then you will move to create more complex visualizations and customize them. Finally, make customized calculations using DAX, which is a Microsoft formula language.

Here is the link to join this course for FREE — Introduction to Power BI

7. Introduction to Data Visualization with Matplotlib [FREE]

Python is a good language to learn when you want to visualize your data. There are a dozen of the library to achieve this goal, and matplotlib is one of them.

This course will help you learn to use the matplotlib pyplot interface and create a simple visualization and customize that data appearance.

And you will learn how to visualize your time-series data, which helps you clarify the trends and discover the relationship between them. Finally, learn to visualize the quantitative visualization and share your work with others.

Here is the link to join this course for FREE — Introduction to Data Visualization with Matplotlib

8. Introduction to Data Visualization with Seaborn [FREE]

Many available visualization libraries for python language, and another one used a lot for statistical visualization and customization is known as seaborn, which is used a lot among data analysts.

You will learn to create a scatter plot and count and plots using the most capability of seaborn, which is adding a third variable to your plot. Later, you will learn to visualize two quantitative and categorical variables and customize your seaborn plots.

Here is the link to join this free course — Introduction to Data Visualization with Seaborn

All these online courses are free and you can use them to learn Python, SQL, and R. Rest of them are not free because they are very specialized and high-quality courses and you would need a Datacamp subscription to access those courses, but you can always check the first chapter for free by using free Datacamp account.

4 Best Paid Courses to learn Machine Learning and Deep Learning in Datacamp in 2026

So far, we have looked at the free Datacamp course to learn essential data skills like Python, SQL, R programming, Excel, Seaborn, Data Visualization and more but Datacamp also have great in-depth courses which are not free but definitely worth checking.

Here is a list of best Datacamp courses to learn Machine Learning and Deep Learning in depth in 2026:

1. Introduction to Deep Learning in Python

If you want to be an AI engineer or a data scientist, you should definitely learn deep learning used in many fields such as robots, self-driving cars, natural language processing, and more.

DataCamp has created a course that teaches you these skills using the Python language and Keras library, starting with the basics of neural networks and their concepts like the activation function.

Then, it will learn how to optimize your model. Later create a neural network with Keras and evaluate your model.

Here is the link to join this course — Introduction to Deep Learning in Python

2. Introduction to Data Visualization with Matplotlib

Data visualization is where you can convert the data into plots and charts to understand more about your data in one picture. This skill is mandatory if you want to be a data scientist, data analyst, or even an AI engineer.

DataCamp has created a course that teaches you this skill using Python and matplotlib. It starts by understanding the matplotlib interface, creating some plots and customizing them, plotting time-series data and bar charts, and statistical plotting.

Here is the link to join this course — Introduction to Data Visualization with Matplotlib

3. Supervised Learning with scikit-learn

In supervised learning, you use labeled data to train your model and make a prediction, so you have to learn machine learning if you are planning to be a data scientist and this course teaches you how to perform this using the sci-kit-learn.

You will also learn how to solve classification problems then move to solve problems with regression. Later, learn how to evaluate your model and improve it.

Here is the link to join this course for FREE — Supervised Learning with scikit-learn

4. Unsupervised Learning in Python

Unsupervised learning is another type of machine learning that you need to learn. Here, the model will analyze and cluster unlabeled datasets and be used in customer segmentation and grouping your data according to its similarity.

DataCamp has created a course on unsupervised learning using the sci-kit-learn and scipy, starting by learning the clustering techniques and applying them to the stock market prices, then learning how to visualize hierarchy and learn the dimension reduction techniques more.

Here is the link to join this course — Unsupervised Learning in Python

By the way, you would need a Datacamp account to access this course. Creating a Datacamp account is free for learners and you also get free access to all of their 350+ courses first chapter.

It also comes with 7 projects but for the best learning experience, I recommend their personal plan which you can get for just $25 per month. This gives access to all of their courses and projects as well as certifications.

Note — They are also offering a whopping 63% discount now, you can take advantage of that to level up and learn in-demand Data Skills in 2026

That’s all about the best and free Datacamp courses to learn Python, Data Science and other in-demand Data skills in 2026. Whether you are a university student learning Python, SQL, and Data science or just an amateur who wants to learn this field through online courses and get certified, the certificate of DataCamp is 100% worth it.

You can include them in your resume if you are looking for a job. They are also very engaging and hands-on to learn these in-demand essential skills. I highly recommend Datacamp to anyone learning Python, Data Science, or SQL.

Other Python Articles and tutorials you may like:

Thanks for reading this article so far. If you find these best Python, SQL, and Data science training courses from DataCamp useful, please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. — If you are looking for a free Datacamp course to learn Data Science, I suggest you check out Data Science for Everyone, a free course from Datacamp that provides an introduction to Data Science without any coding headache. Great for beginners and experienced people who want to learn Data Science in 2026

10 Free Data Science Online Courses for Beginners to Join in 2026

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I Tried 30+ Frontend Masters Courses: Here Are My Top 5 Recommendations for 2026

2026-04-03T20:50:00.000-07:00

Hello guys, in the fast-paced and ever-evolving field of web development, continuous learning is not just beneficial — it’s essential.

Staying ahead of the curve requires an ongoing commitment to expanding your skillset, understanding new technologies, and mastering the tools that drive modern web applications.

For developers looking to elevate their expertise and career prospects in 2026, Frontend Master offers some of the most comprehensive and engaging courses available.

Frontend Master has established itself as a premier online learning platform, known for its high-quality, in-depth courses tailored to both beginners and experienced developers.

Whether you’re aiming to grasp the fundamentals of web development, delve into complex algorithms, or master a powerful front-end library like React, Frontend Master has a course designed to meet your needs.

In this article, we’ll explore the top 5 Frontend Master courses you should consider taking in 2026. These courses have been selected based on their relevance, comprehensiveness, and the practical skills they impart.

From mastering algorithms and JavaScript to becoming proficient in React and understanding the full stack, these courses will equip you with the knowledge and hands-on experience needed to excel in the competitive world of web development.

Let’s dive in and discover how each of these courses can help you achieve your learning and career goals.

By the way, if you are in hurry, then you can just go and join Frontend Masters now, you will thank me later after watching their high-quality courses.

They are also offering 17% discount on their annual plan. This is a rare opportunity to get access of 200+ premium courses, guided learning paths, and new platform features, all at a fraction of the cost.

Whether you want to master JavaScript, React, or DevOps, now’s the time to join and level up your skills. Don’t miss out — the sale ends on 18th September!

👉 Join today and save 17% on your yearly membership!

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5 Best Frontend Masters courses for Web Developers in 2026

Here is a list of best courses web developers can join in Frontend masters to learn essentials web development skills like JavaScript and React.

1. The Last Algorithms Course You’ll Need

Algorithms are the backbone of efficient programming, and mastering them can significantly elevate your problem-solving skills.

“The Last Algorithms Course You’ll Need” is designed to provide an in-depth understanding of algorithms, covering everything from basic sorting and searching to advanced topics like dynamic programming and graph algorithms.

Key Highlights:

Comprehensive Curriculum: This course covers a wide range of algorithms, ensuring that you are well-equipped to tackle any coding challenge.
Hands-on Learning: With numerous coding exercises and real-world problems, you’ll gain practical experience in implementing algorithms.
Expert Instruction: Taught by seasoned professionals, the course offers insights and tips that you won’t find in textbooks.

Why You Should Enroll:

Mastering algorithms not only enhances your coding efficiency but also prepares you for technical interviews and competitive programming.

This course ensures that you have a solid foundation in algorithms, making it a must-have for any developer’s skillset.

Here is the link to join this course — The Last Algorithms Course You’ll Need

2. JavaScript: From First Steps to Professional

JavaScript is the lingua franca of the web, and proficiency in it is essential for any front-end developer.

The “JavaScript: From First Steps to Professional” is a comprehensive course that takes you from the basics of JavaScript to advanced concepts, making you a proficient JavaScript developer.

Key Highlights:

Beginner to Advanced: The course starts with the fundamentals of JavaScript and progressively covers advanced topics like closures, prototypes, and asynchronous programming.
Project-Based Learning: You’ll build real-world projects that reinforce your learning and demonstrate your skills.
Modern JavaScript: The course covers the latest features of JavaScript, including ES6+ syntax and features.

Why You Should Enroll:

JavaScript is at the heart of modern web development. This course provides a thorough grounding in JavaScript, ensuring that you are well-prepared to develop dynamic and interactive web applications.

Here is the link to join this course — JavaScript: From First Steps to Professional

3. Complete Intro to React, v8

React has become one of the most popular libraries for building user interfaces.

The “Complete Intro to React, v8” is the definitive course for learning React, covering everything from the basics to advanced concepts like hooks, context, and performance optimization.

Key Highlights:

In-Depth React: The course covers the core concepts of React, including JSX, state, props, and lifecycle methods.
Modern React Practices: You’ll learn about the latest React features such as hooks and context API, ensuring you stay current with industry practices.
Practical Projects: By building a series of projects, you’ll gain hands-on experience in creating React applications.

Why You Should Enroll:

React is a powerful tool for building dynamic web applications. This course equips you with the skills needed to create complex and performant React applications, making you a valuable asset to any development team.

Here is the link to join this course — Complete Intro to React, v8

4. Full Stack for Front-End Engineers, v3

Understanding the full stack is crucial for front-end engineers who want to build robust and scalable web applications. “Full Stack for Front-End Engineers, v3” bridges the gap between front-end and back-end development, providing a comprehensive understanding of both.

Key Highlights:

Comprehensive Coverage: The course covers front-end technologies like React and back-end technologies like Node.js, Express, and databases.
Real-World Applications: You’ll build full-stack applications, gaining practical experience in integrating front-end and back-end components.
Deployment and DevOps: Learn how to deploy your applications and manage them in a production environment.

Why You Should Enroll:

Full-stack knowledge allows you to understand and contribute to the entire development process, from design to deployment. This course empowers you with the skills to build and maintain complete web applications, enhancing your versatility as a developer.

Here is the link to join this course — Full Stack for Front-End Engineers, v3

5. Complete Intro to Web Development, v3

For those new to web development, “Complete Intro to Web Development, v3” offers a comprehensive introduction to the field. This course covers the essential technologies and concepts needed to build modern web applications, from HTML and CSS to JavaScript and beyond.

Key Highlights:

Foundational Skills: Learn the basics of HTML, CSS, and JavaScript, the core technologies of web development.
Interactive Learning: The course includes interactive coding exercises and projects to reinforce your learning.
Modern Web Development: Get introduced to modern web development practices and tools, including responsive design and version control with Git.

Why You Should Enroll:

This course provides a solid foundation in web development, making it ideal for beginners. By the end of the course, you’ll have the skills needed to build your own web applications and continue your learning journey in more advanced topics.

Here is the link to join this course — Complete Intro to Web Development, v3

Conclusion

That’s all about the 5 Best Frontend Masters courses to Learn Web Development in 2026. Investing in your education and skills is one of the best ways to advance your career in web development.

These top 5 Frontend Masters courses for 2026 offers a blend of theoretical knowledge and practical experience, ensuring that you are well-prepared to tackle the challenges of modern web development.

Whether you’re looking to master algorithms, become proficient in JavaScript, dive into React, understand the full stack, or get started with web development, these courses have you covered.

Enroll today and take the next step in your development journey!

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Thank you for reading this article so far. If you like these frontend masters courses and my review then please share with your friends and colleagues. If you have any questions or doubts then feel free to ask.

P. S. — If you are keen to level up your frontend skills then joining frontend master can be a great first step as they have awesome courses to learn valuable frontend skills. 👉 Join today and save 17% on your yearly membership!

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Best Java Fundamentals Course in 2026? Angie Jones on Frontend Masters Reviewed

2026-04-02T20:52:00.000-07:00

Hello guys, today I am going to review a Java course from Frontend Master created by none other than, Java Champion, Angie Jones.

I was initially surprised to find this course on Frontend Maser because I always thought Frontend Master is more about JavaScript and related technologies.

As I said, For long time, I thought Frontend Masters is just for frontend web development but I was pleasantly surprised to find the backend related course, particularly one which is focused on Java and even more because it was created by Angie who I have been following on Twitter for a long time.

Anyway, Frontend Masters is renowned for providing high-quality programming courses, and “Java Fundamentals” is no exception. Similar to frontend masters popular web development courses, this one is also a gem and one of the best online courses to learn Java.

In this article, we will delve into the course content, instructor credentials, teaching approach, and the overall value it provides to help you determine if it’s worth your investment.

Review — Is Java Fundamentals by Angie Jones on Frontend Masters worth it?

The “Java Fundamentals” course on Frontend Masters, taught by Angie Jones, aims to equip beginners and individuals seeking to refresh their Java skills with a solid foundation in Java programming.

The course covers crucial concepts, syntax, and best practices necessary for building Java applications.

1. Instructor Credentials — Who is Angie Jones?

If you don’t know, Angie Jones is a distinguished software engineer, automation expert, and international speaker with extensive experience in the industry.

She has worked for notable tech companies such as IBM, Twitter, and Apple, specializing in Java programming and automation testing.

She is also one of the popular Java champion and runs testautomation site for quite sometime where he provide training on Java to automation tester.

Angie’s expertise and professional background make her a suitable instructor for the “Java Fundamentals” course.

2. Course Content and Structure

The course is structured to cover Java fundamentals systematically. It starts with an introduction to Java, explaining its benefits and how it fits into the programming landscape.

From there, it delves into key topics such as variables, data types, control flow, object-oriented programming principles, exception handling, input/output operations, and more.

Angie Jones ensures that each concept is explained clearly and provides practical examples to illustrate their usage. The course also includes coding exercises and quizzes to help reinforce learning and test your understanding of the material.

The course content is structured systematically to cover Java fundamentals comprehensively. Here’s an overview of the topics covered:

Introduction
Angie Jones introduces the course, provides her professional background, and guides learners through the setup process, including installing IntelliJ and Java.

Conditions & Loops
This section covers essential concepts such as variables, control flow, if statements, switch statements, loops (while, do-while, and for), and nested loops.

Methods, Objects & Data Types:
Angie delves into methods, object-oriented programming principles, variable scope, constructors, instantiating objects, sending and receiving objects, records, wrapper classes, and more.

Arrays & Text Processing
This section explores arrays, random number generation, working with strings, text blocks, and string manipulation using StringBuilder.

Inheritance
Angie covers the topic of inheritance, discussing how classes extend other classes, overriding methods, overloading methods, limiting access, and sealed classes.

Polymorphism & Abstraction
In this part, you will understand polymorphism, type casting, instanceof operator, abstract classes, interfaces, and multiple inheritance.

Data Structures
This segment provides an overview of Set, List, Queue, and Map data structures, along with their usage and operations.

Functional Interfaces & Streams
Angie introduces functional interfaces, streams, intermediate and terminal operations, filtering, mapping, reducing, and utilizing the collect operation.

Exceptions
Error handling is an important part of processional coding and in this part you will learn exception handling, checked and unchecked exceptions, multiple exception handling, file handling, throwing and rethrowing exceptions.

Teaching Approach

Angie Jones employs an engaging teaching style, breaking down complex concepts into easily understandable parts.

She emphasizes practical applications of Java, illustrating real-world scenarios and best practices.

The course includes coding exercises, demonstrations, and explanations to ensure learners comprehend the material thoroughly.

Value and Benefits

One of the thing you should look before joining any course is the value it provide as there are a lot of option of and you cannot try everything. The “Java Fundamentals” course on Frontend Masters offers several benefits:

1.Comprehensive Coverage
The course covers a wide range of fundamental Java topics, providing a solid foundation for further Java development or automation testing.

2. Practical Examples
Angie Jones focuses on real-world applications and industry best practices, enabling learners to understand how Java concepts are implemented in professional scenarios.

3. Experienced Instructor
If you don’t know Angie is a Java Champion and also running test automation training for a long time. With Angie Jones’ industry expertise and extensive experience in Java programming, learners can benefit from her valuable insights and guidance.

5. Interactive Learning
The course incorporates coding exercises, quizzes, and demonstrations, allowing learners to actively participate, reinforce their understanding, and assess their progress.

6. Reputation and Platform Quality
Frontend Masters has a strong reputation for delivering high-quality courses, ensuring that the “Java Fundamentals” course maintains a standard of excellence.

Here is the link to join this course — “Java Fundamentals”

Conclusion

That’s all about this awesome course to learn Java on Frontend Masters. The “Java Fundamentals” course by Angie Jones on Frontend Masters is a valuable investment for beginners and those seeking to enhance their Java programming skills.

Angie’s expertise, the course’s comprehensive content, practical examples, and interactive learning approach provide learners with a solid foundation in Java.

While the course offers substantial value, supplementing it with additional practice, resources, and real-world projects will further enhance your skills and proficiency in Java programming.

You can learn more about this course here — “Java Fundamentals”

Java Fundamentals | OOP & Functional Programming in Java | Course by Angie Jones

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Thank you for reading this article till the end. If you like these Frontend masters courses then please share with your friends and colleagues. If you have any questions or doubts then feel free to ask.

P. S. — If you are keen to level up your frontend skills then joining frontend master can be a great first step as they have awesome courses to learn valuable frontend skills, you can join Frontend Masters now and even get a 17% discount on their annual plan.

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I Tried 30+ Prompt Engineering Courses: Here Are My Top 5 Recommendations for 2026

2026-04-02T08:19:00.000-07:00

Hello guys, as AI taking over the coding world, prompt Engineering is quickly becoming one of the most valuable skills for software developers like you and me.

Whether you’re working with ChatGPT, Claude, Gemini, or any other large language model (LLM), your ability to craft effective prompts directly affects the quality and accuracy of the AI’s response.

As companies, both big and small, from banks to services based companies like TCS and Infosys, increasingly adopt AI tools to boost productivity, the demand for professionals who understand how to communicate effectively with these models is skyrocketing.

But here’s the catch — — Prompt Engineering is not just about giving instructions. It’s a hybrid skill that blends creativity, logic, programming literacy, and a deep understanding of how language models work.

Whether you’re a Software developer, web developer, a data analyst, content creator, or product manager, knowing how to structure prompts gives you a competitive edge.

Earlier, I have shared best AI courses, best ChatGPT courses, best Data Science courses and best Machine Learning courses and in this article, I am going to share best Udemy courses to learn Prompt Engineering in 2026.

Udemy, with its vast collection of affordable and high-quality courses, is one of the best platforms to start or deepen your prompt engineering journey.

In this post, I’ve curated the 7 best Udemy courses to learn Prompt Engineering in 2026, based on depth, relevance, instructor experience, and hands-on value.

By the way, if you are in rush then you can just go ahead and start with ChatGPT: Complete ChatGPT Course For Work 2026 (Ethically)! course on Udemy. This is the latest and most up-to-date course on ChatGPT on Udemy.

5 Best Prompt Engineering courses on Udemy in 2026

Without any further ado, here are the best prompt engineering courses you can join on Udemy in 2026

1. The Complete Prompt Engineering for AI Bootcamp (2026)

This course is a comprehensive guide not only to ChatGPT and prompting, but also GitHub Copilot.

In this course, you will learn practical coding skills for working professionally with AI, including GPT-4, Stable Diffusion, and GitHub Copilot.

It’s great for learners who want to explore a variety of AI tools and understand how prompt structures differ across use cases.

What you’ll learn:

ChatGPT 4 prompt writing techniques
Prompting for creative tasks vs analytical tasks
Using GitHub Copilot for code generation.
AI prompt strategies for entrepreneurs and freelancers
Learn the “Five Principles of Prompting”, as well as common tips & tricks for professional grade output.

Here is the link to join this course — — The Complete Prompt Engineering for AI Bootcamp (2026)

2. Practical Prompt Engineering Masterclass: Hands-On Learning

Created by Asif Farooqui, this course focuses solely on mastering the art and science of Prompt Engineering. The instructor emphasizes real-world examples, which makes it highly practical.

What you’ll learn:

Prompt templates for different professional use cases
How to debug prompts when results go wrong
Prompt Engineering ethics and limitations
Role prompting and chain-of-thought strategies

Here is the link to join this course — — Practical Prompt Engineering Masterclass: Hands-On Learning

3. ChatGPT Masterclass: The Guide to AI & Prompt Engineering

This is one of the most in-depth courses for developers. It blends theory with applied use cases and includes prompt crafting for software development, product design, and marketing content.

What you’ll learn:

Zero-shot, one-shot, few-shot prompting
Using ChatGPT with APIs for task automation
Prompt strategies for code generation and debugging
Building tools on top of GPT-based APIs

Here is the link to join this course — — ChatGPT Masterclass: The Guide to AI & Prompt Engineering

4. The Complete AI Guide: Learn ChatGPT, Generative AI & More

Perfect for beginners and non-coders. This course focuses on everyday productivity tools powered by AI and how to use ChatGPT for tasks like writing, email automation, summarization, and brainstorming.

Most importantly you will learn to combine the power of ChatGPT with programming fundamentals, algorithms, debugging, and documentation!

What you’ll learn:

Prompt frameworks like PASTOR and ACT
Best practices for business communication
Tools like Notion AI, Google Bard, and ChatGPT
Case studies in marketing and HR

Here is the link to join this course — — The Complete AI Guide: Learn ChatGPT, Generative AI & More

5. ChatGPT Complete Course — — Prompt Engineering for ChatGPT

This one is a very accessible introduction with a step-by-step approach. This course is aimed at complete beginners and teaches you how to think like a prompt engineer.

What you’ll learn:

Core building blocks of an effective prompt
Structured and iterative prompt techniques
Common pitfalls and how to avoid vague outputs
Role-based prompting for personas

Here is the link to join this course — — ChatGPT Complete Course — — Prompt Engineering for ChatGPT

6. LLM Engineering: Master AI, Large Language Models & Agents

This course is ideal for developers and engineers looking to build LLM-powered apps. It focuses on using LangChain — — a framework that allows advanced orchestration of prompts and memory with OpenAI.

What you’ll learn:

Prompt templates with LangChain
Contextual memory and chaining techniques
Integration with OpenAI API
Building chatbots and autonomous agents

Here is the link to join this course — — LLM Engineering: Master AI, Large Language Models & Agents

7. Prompt Engineering: Getting Future Ready (1000+ Prompts inc)

This course targets intermediate to advanced users who want to go beyond simple prompting. It covers the latest techniques like prompt chaining, few-shot learning, and integrating tools with ChatGPT.

It share 1000+ prompts you can use for various things like coding, testing and product development. You will also learn to create thousands of unique prompts for ChatGPT, Stable Diffusion, DALL-E, and MidJourney.

What you’ll learn:

Prompt patterns for specific outcomes
Combining tools (Python, APIs) with LLM prompts
Evaluation techniques for prompt success
Building smart workflows and agents

Here is the link to join this course — — Prompt Engineering: Getting Future Ready (1000+ Prompts inc)

Why Learn Prompt Engineering in 2026?

In order to show you why should learn prompt engineering let me show you both good and bad prompts and the output generated by them

Here’s the difference between good and bad prompts specifically for coding tasks:

Good Coding Prompt Example

Create a Python function that calculates the Fibonacci sequence up to n terms. The function should:

Accept a parameter ’n’ (number of terms)
Include input validation to handle negative numbers and non-integers
Return the sequence as a list
Use recursion with memoization for efficiency
Include docstrings and comments explaining the implementation
Include 2–3 example test cases showing different inputs

My experience level is intermediate Python, so please explain any complex optimization techniques used.

Why it’s good:

Specific language: Clearly states Python
Well-defined task: Calculate Fibonacci sequence up to n terms
Technical requirements: Lists specific implementation details
Performance considerations: Mentions efficiency (recursion with memoization)
Documentation needs: Requests docstrings and comments
Testing approach: Asks for example test cases
Provides context: Mentions user’s experience level
Asks for explanations: Requests clarification of complex concepts

Bad Coding Prompt Example

Write code for Fibonacci.

Why it’s bad:

Ambiguous language: No programming language specified
Unclear requirements: Doesn’t specify what aspect of Fibonacci to implement
No performance guidelines: Doesn’t mention efficiency concerns
No error handling requirements: Doesn’t address edge cases
No documentation requirements: Doesn’t request comments or explanations
No context: Doesn’t mention user’s experience level or use case
No specific output format: Doesn’t specify return type or how to present results

Let me show you these functions to further illustrate the difference in the outputs you’d see.

Here is output from bad prompt first

and here is output from good prompt

You can see how the code from the good prompt includes comprehensive documentation, error handling, optimization through memoization, and thorough test cases — while the result from the bad prompt is minimal, lacks documentation, and provides only basic functionality.

That explains why its important for developers to learn aobut prompt engineering in 2026.

Prompt Engineering Cheat Sheet

And, here is the Prompt Engineering Cheat sheet I promised at the start. This shows key prompt engineering techniques and tips you can use to leverage LLM like ChatGPT or Claude better

Final Thoughts

Prompt Engineering is not just a technical skill — — it’s a mindset. As LLMs become embedded in every aspect of software, business, education, and content creation, your ability to instruct and guide them effectively will determine your success.

Udemy’s wide range of affordable, up-to-date courses gives learners the chance to master this futuristic skill no matter their background.

Whether you’re a beginner exploring what ChatGPT can do or a developer building LLM-powered applications, one of these 7 courses will be the perfect next step in your learning journey.

Other AI, LLM, and Machine Learning resources you may like

Thanks a lot for reading this article so far, if you like these courses then please share with your friends and colleagues. If you have any feedback or questions then please drop a note.

P.S. You can also join a course like LLM Engineering: Master AI, Large Language Models & Agents to get some hands-on experience on building RAG based chatbot and learning LLM by watching. Don’t wait for your company to start using AI. Learn now, lead later.

10 Essential AI Tools Every Developer Should Learn in 2026

2026-04-01T08:15:00.000-07:00

Hello guys, the way we write code is changing — fast, I mean very fast. Gone are the day where you create one class in one day with advancement in AI, now you can create the whole application in 1 hour.

AI coding tools, sometimes referred to as “vibe coding” platforms, are revolutionizing software development.

Whether you’re building full-stack apps, testing code, debugging, or deploying infrastructure, there’s now an AI tool to make it faster, smarter, and easier.

As a software engineer who’s spent hundreds of hours working with Copilot, Replit, and emerging tools like Cursor and CodeWhisperer, I can confidently say: learning these platforms is no longer optional — it’s essential.

In this post, I’ll break down 10 AI coding tools every developer should get familiar with in 2026, and I’ll recommend a top Educative.io course to help you master each one.

Whether you’re a backend developer, front-end dev, or full-stack engineer, this guide is for you.

By the way, if you are new to Generative AI then I also suggest you to go through a Gen AI course like Generative AI Handbook to start with. It will help interact better with LLM.

Generative AI Handbook

Explore key concepts and applications of modern AI systems in the GenAI Handbook.

www.educative.io

10 Best AI Tools Software Developers Should Learn in 2026

Without any further ado, here are the best AI coding tools you can use right now for coding, generating unit tests, debugging and even designing your software application.

1. Claude Code by Anthropic

Claude Code, developed by Anthropic, is a powerful AI coding assistant built into the Claude family of large language models.

Known for its conversational abilities, Claude excels in understanding code context, suggesting clean refactors, explaining complex logic, and even generating entire functions or modules from natural language prompts.

It offers intelligent, thoughtful code generation, refactoring, and debugging using natural language.

💡 Why learn it? Claude stands out for its safe, conversational approach to coding tasks — great for developers who want accuracy and context over speed.
🎓 Recommended course: Claude Code: Building Faster with AI, from Prototype to Prod

2. GitHub Copilot

The OG of AI code assistants. GitHub Copilot writes code in real time as you type — it’s like pair programming with a superpowered dev.

💡 Why learn it? It can save hours of boilerplate, suggest APIs, and even write test cases.

🎓 Recommended course: Mastering GitHub Copilot

Master GitHub Copilot - AI-Powered Course

Learn GitHub Copilot foundations through hands-on lessons: explore AI-assisted coding, Copilot chat, prompt…

www.educative.io

3. Cursor

A new kind of AI code editor built for serious devs. Cursor uses GPT-4, understands your codebase, and can help you refactor, explain, or even debug your code inside VS Code.

💡 Why learn it? It feels like VS Code with ChatGPT baked in — and it’s optimized for real-world codebases.

🎓 Recommended course: Build Smarter Code with Cursor AI

Learn Cursor AI: Code Smarter and Build Anything with AI

This course covers how Cursor uses integrated AI tools to help modern developers speed up coding, debugging, and…

www.educative.io

4. Replit Ghostwriter

Replit has evolved into an all-in-one cloud IDE with AI assistance. Ghostwriter helps generate, explain, and fix code within your browser.

💡 Why learn it? Perfect for hackathons, building prototypes, or running quick scripts in the cloud.

5. Amazon Q Developer for Programmers and DevOps AWS AI coding

Amazon’s answer to Copilot. Amazon Q Developer works across AWS services and helps generate secure, production-ready code.

💡 Why learn it? Ideal for devs in AWS ecosystems or working on cloud-native apps.

6. Tabnine

Tabnine uses LLMs fine-tuned on your codebase. It’s great for enterprises concerned with privacy and teams working on private repos.

💡 Why learn it? If you’re working in a team with security needs, Tabnine offers on-premise options.

🎓 Recommended course: Vibe Coding with ChatGPT, GitHub Copilot, Tabnine & More

7. ChatGPT

ChatGPT is still the best conversational AI model that has transformed how we interact with artificial intelligence, offering natural language understanding and generation capabilities for diverse applications ranging from content creation to complex problem-solving and code assistance.

💡 Why learn it? ChatGPT has become an essential tool for professionals across all domains. Mastering its capabilities gives you a significant competitive advantage in productivity and innovation.

8. Codeium

A free and blazing-fast AI coding assistant that integrates into JetBrains, VS Code, and more.

💡 Why learn it? It’s lightweight, accurate, and great for developers who want an alternative to Copilot.

9. CrewAI

A cutting-edge framework for orchestrating role-playing autonomous AI agents, enabling teams of AI agents to collaborate effectively on complex tasks with defined roles, goals, and backstories.

CrewAI Agents now have the powerful ability to write and execute code, significantly enhancing their problem-solving capabilities Coding Agents — CrewAI.

You can enable this by setting the allow_code_execution parameter for agents.

💡 Why learn it? CrewAI represents the next evolution in multi-agent systems. It’s perfect for creating collaborative AI teams that can handle enterprise-level challenges.

10. Code Interpreter / GPT-4 Advanced Data Analysis

This is the power tool for data analysis, debugging, and algorithm tracing. OpenAI’s Code Interpreter can run Python code, create charts, and help you debug in real-time.

💡 Why learn it? Perfect for algorithmic thinking, debugging, and test-driven development.

11. OpenDevin

An open-source AI software agent designed to perform real-world dev tasks by combining planning, file editing, and terminal use.

💡 Why learn it? OpenDevin is a step toward AI agents that can code entire apps. Get in early.

🎓 Recommended course: AI Agents for Developers: Getting Started with OpenDevin

Final Thoughts

Whether you’re a new developer or a senior engineer, learning how to use these AI-powered coding tools will give you a serious edge in 2026. The game is no longer about typing fast — it’s about thinking clearly, prompting smartly, and letting AI amplify your output.

Explore any of the Educative courses above to get hands-on with these tools. You’ll not only save time — you’ll become a more productive, creative, and forward-thinking developer.

By the way, you would need an Educative subscription to join this course, which cost around $14.99 but also provide access to more than 1000+ courses, projects, and cloud labs to learn in-demand tech skills including web development.

Educative Unlimited: Excel with AI-Powered Learning

Ready to level up your career? Lock in unlimited access to Educative's entire library of 1200+ hands-on Courses…

www.educative.io

You can also use 7 days free trial to get this course for FREE.

Educative Free Trial: Accelerate your career

Level up your coding skills. No more passive learning. Interactive in-browser environments keep you engaged and test…

www.educative.io

Other Awesome Resources from Educative.io You may like

Thanks for reading this article so far. If you like these AI, ML and LLM Engineering courses then please share with your friends and colleagues. If you have any questions or suggestions feel free to leave a comment.

P. S. — If you are new to AI and LLM Engineering worth then I also suggest you to go through this Machine Learning Handbook and Generative AI Handbook, both are great resources for any who want to learn Artificial Intelligence in depth.

Generative AI Handbook

Explore key concepts and applications of modern AI systems in the GenAI Handbook.

www.educative.io

7 Project Based Courses to Master AI Engineering in 2026

2026-03-31T08:05:00.000-07:00

credit — DecodingML

Hello guys, as I have said before, Artificial Intelligence is no longer just an academic subject or a futuristic concept — it’s the core of modern software engineering.

And in 2026, as companies continue to seek professionals who can actually build and deploy AI-powered systems, one thing is becoming increasingly clear:

Learning through projects isn’t optional anymore — it’s essential.

Many aspiring AI engineers fall into the trap of watching endless tutorials or reading technical documentation without ever building something tangible.

But if you’re serious about becoming an AI engineer, there’s no better way to sharpen your skills and prove your capabilities than by working on real-world projects.

Whether you’re learning about Large Language Models (LLMs), AI agents, or generative AI, project-based learning allows you to apply concepts, solve real challenges, and build a portfolio that hiring managers want to see.

In the past, have shared best AI courses, books, and AI frameworks and libraries, and in this article, I am going to share best Udemy courses to learn AI and LLM Engineering with projects, yes that’s the key part, building projects.

10 Artificial Intelligence and LLM Books Every Software Engineer Should Read in 2026

10 Must read AI and LLM Engineering books for Software Engineers who want to become an AI Engineers.

medium.com

10 AI Frameworks and Libraries Every Developer Should Learn in 2026

My favorite Udemy courses to learn how to build RAG applications using Python and LangChain in 2026

medium.com

7 Best Udemy Courses to learn AI and LLM Engineering with Projects in 2026

Here are the top 7 project-based Udemy courses for AI engineers in 2026. These courses don’t just teach — — they make you build. If you’re aiming to break into AI or level up your engineering game, these courses are your launchpad.

1. The Complete Agentic AI Engineering Course (2026)

Students: 60,154+
Projects: 8 real-world agentic AI projects using OpenAI Agents SDK, CrewAI, LangGraph, AutoGen, and MCP

This is one of the most exciting and well-structured courses for building agentic AI systems — — the future of autonomous applications. You’ll build multiple real-world projects, ranging from task automation bots to multi-agent workflows using modern tools like:

OpenAI Agents SDK
LangGraph (for complex control flows)
AutoGen & CrewAI (for managing multiple agents)
MCP (for orchestrating tools and resources)

By the end of the course, you’ll not only know how to build AI agents but also when and why to use them effectively. If you’re looking to break into advanced AI engineering with agent-based systems, this course is a must.

✅ Ideal for: Intermediate to advanced learners who want to specialize in multi-agent and agentic systems.

Here is the link to join this course — — The Complete Agentic AI Engineering Course

2. LLM Engineering: Master AI, Large Language Models & Agents

Students: 111,423+
Projects: Build and deploy 8 LLM-powered apps

This bestseller udemy course is perfect if you want to go deep into the Large Language Model (LLM) ecosystem. You’ll explore not just the theory behind models like GPT, but build full applications powered by:

Generative AI
RAG (Retrieval-Augmented Generation)
LoRA (Low-Rank Adaptation)
LangChain and Hugging Face

What sets this course apart is its real deployment scenarios — — you’ll learn how to integrate LLMs with APIs, cloud services, and UI layers. By completing the included projects, you’ll have a deployable portfolio to show off your skills.

✅ Ideal for: Developers aiming to work on LLM-based applications or productized AI tools.

Here is the link to join this course — — LLM Engineering: Master AI, Large Language Models & Agents

3. Master LLM Engineering & AI Agents: Build 14 Projects — 2026

Students: 1,551+
Projects: 14 high-quality AI engineering projects

If you’re serious about building a diverse portfolio, this course delivers in a big way.

It walks you through 14 complex projects covering everything from LangGraph orchestration, RAG pipelines, to MCP-based systems, and integrations with CrewAI, N8N, AutoGen, and Hugging Face Transformers.

You also get:

Expert mentorship and Q&A support
Access to a community of AI engineers
Advanced use cases in business and personal automation

This course is incredibly hands-on and fast-paced — — perfect for someone preparing for a career transition or actively looking to impress recruiters.

✅ Ideal for: Experienced developers who want to build a wide range of AI projects and break into LLM + Agent development roles.

Here is the link to join this course— Master LLM Engineering & AI Agents: Build 14 Projects— 2026

4. Building Gen AI App: 12+ Hands-on Projects with Gemini Pro

Students: 16,695+
Projects: 12+ Generative AI apps using Gemini Pro and LangChain

This course is your go-to resource for mastering Google’s Gemini Pro models and applying them in LangChain pipelines to build creative and enterprise-ready solutions.

Projects range from:

Text summarization tools
AI content generators
Search engines powered by Gemini
Document question-answering bots

If you want to learn how to work with Gemini models and create practical tools with the latest GenAI capabilities, this course is both future-proof and incredibly valuable.

✅ Ideal for: Developers and product designers who want to work with Gemini and integrate it into end-user applications.

Here is the link to join this course — — Building Gen AI App: 12+ Hands-on Projects with Gemini Pro

5. Modern Artificial Intelligence Masterclass: Build 6 Projects

Students: 38,072+
Projects: 6 practical AI projects in Finance, Tech, Art, and Healthcare

If you prefer real-world problem solving, this course blends project-based learning with industry relevance. You’ll build six end-to-end AI systems, including:

A stock market prediction tool
Medical image analysis
An AI-powered art generator
A recommendation engine

The course focuses on interpretable AI, Python frameworks (like TensorFlow & Scikit-learn), and model evaluation, making it great for those interested in both machine learning and explainability.

✅ Ideal for: Beginners to intermediate learners who want project experience in multiple sectors and domains.

Here is the link to join this course — — Modern Artificial Intelligence Masterclass: Build 6 Projects

6. AI Automation: Build LLM Apps & AI-Agents with n8n & APIs

Students: 25,784+

Projects: Automate workflows with LLMs, n8n, RAG, DeepSeek, Ollama

This course dives into the intersection of automation and AI, teaching you how to create intelligent workflows using n8n, OpenAI APIs, and LLMs like DeepSeek, Ollama, and Gemini.

Projects focus on:

Workflow automation (emails, forms, tasks)
Creating RAG-based chatbots
Business agent orchestration
End-to-end AI pipelines using APIs and low-code tools

It’s perfect if you want to automate business processes or create tools for startups and solo ventures.

✅ Ideal for: Solopreneurs, automation enthusiasts, or business developers integrating AI into workflows.

Here is the link to join this course — — AI Automation: Build LLM Apps & AI-Agents with n8n & APIs

7. Complete MLOps Bootcamp With 10+ End-to-End ML Projects

Bestseller | 23,871 students enrolled

If you’re aiming to go beyond building ML models and actually deploy and maintain them in production, this is the course to take.

You’ll cover:

Model versioning and tracking
CI/CD pipelines for ML (with GitHub Actions, Docker, Kubernetes)
Serving models via FastAPI
Monitoring, alerting, and data drift detection
Building 10+ complete projects, from development to deployment

Why it’s a must-learn:\ AI engineers often neglect MLOps skills. But in 2026, knowing how to deploy, scale, and manage models is as critical as building them. This course ensures you don’t just build a model — — you ship it.

Here is the link to join this course — — Complete MLOps Bootcamp With 10+ End-to-End ML Projects

Final Thoughts: Why You Should Learn AI by Building Projects?

Watching videos is great. Reading books is necessary. But building projects is where the real learning begins. You don’t learn and remember, unless you build things, break things and fix those things.

Here’s why project-based learning is so effective:

You learn by doing: You’re forced to debug, adapt, and understand concepts at a deeper level.
You build a portfolio: Recruiters love seeing GitHub links, live demos, and apps you’ve built.
You gain confidence: Each completed project proves you can build real-world AI systems.
You stay current: Many of these courses teach tools and techniques that are cutting edge in 2026.

If you’re looking to get hired, freelance, or launch your own AI-based product, these Udemy courses provide the best path forward — — with hands-on, high-impact learning.

If you got a lot of time and want to save money, Udemy Personal Plan will be perfect for you.

Final Tip

To make the most of these courses:

Push all your projects to GitHub
Deploy a few on platforms like Vercel, Streamlit, or Hugging Face Spaces
Write blog posts or case studies about what you’ve built

Believe me these small efforts can turn your Udemy course certificates into career-changing assets.

Other AI and Cloud Computing Resources you may like

Thanks for reading this article so far. If you find these Udemy Courses for learning AI and building projects then please share with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. — If you want to learn from books and looking for best AI and LLM Books then I highly recommend you to read AI Engineering by Chip Huyen and The LLM Engineering Handbook by Paul Iusztin and Maxime Labonne, both of them are great books and my personal favorites. They are also highly recommended on Reddit and HN.

10 Artificial Intelligence and LLM Books Every Software Engineer Should Read in 2026

10 Must read AI and LLM Engineering books for Software Engineers who want to become an AI Engineers.

medium.com

I Tried 50+ AI Courses on Udemy: Here Are My Top 10 Recommendations

2026-03-31T01:13:00.000-07:00

Hello guys, if you are not living under the rock in last 2 years then you may have noticed that Artificial Intelligence (AI) is transforming every major industry — — healthcare, finance, education, manufacturing, marketing, and beyond.

As we enter 2026, AI is no longer a buzzword but a must-have skill for developers, data professionals, analysts, and even business leaders.

But starting your AI journey can feel overwhelming: machine learning, neural networks, deep learning, computer vision, NLP — — where do you begin?

If you’re a complete beginner looking to learn Artificial Intelligence from scratch, Udemy offers some of the best beginner-friendly AI courses to help you get started.

Earlier, I have shared best ChatGPT courses, best Data Science courses and best Machine Learning courses and in this article, I am going to share best Udemy courses to learn Artificial Intelligence from Scratch for beginners in 2026.

These courses require no prior experience in AI and cover the foundational concepts, tools, and techniques you need to understand and build intelligent systems.

So what are we waiting for, let’s jump into the best Udemy courses to learn AI in 2026 and start your career in AI engineering or become an LLM Master and get that job you are looking.

10 Best Udemy courses to learn AI from Scratch in 2026

Here are the top 10 Udemy online Courses to Learn Artificial Intelligence for Beginners in 2026:

1. Artificial Intelligence A-Z 2026 : Agentic AI, Gen AI, and RL

This is one of Udemy’s most popular AI courses, teaching the entire pipeline of building an AI from scratch. It focuses on intuition rather than theory — — perfect for those intimidated by complex math.

What you’ll learn:

Building AI with Python
Q-learning and deep Q-learning
AI in games and simulations
Reinforcement learning with hands-on coding

This course is best for absolute beginners who prefer project-based learning over academic theory.

Here is the link to join this course— Artificial Intelligence A-Z 2026: Agentic AI, Gen AI, and RL

2. Artificial Intelligence for Business + ChatGPT Prize [2026]

Tailored for business professionals and non-technical learners, this course explains AI without any coding. It focuses on use cases, ethics, and the impact of AI in business and society.

It also teaches you ChatGPT, one of the most essential tool in this AI age.

Great for:

Entrepreneurs
Managers
Marketing and HR professionals

This course is best for non-coders who want to understand how to apply AI in their careers.

Here is the link to join this Udemy course — Artificial Intelligence for Business + ChatGPT Prize [2026]

3. Complete A.I. & Machine Learning, Data Science Bootcamp

This Udemy course introduces both machine learning and AI fundamentals using simplified explanations and visual learning. It’s great for learners who need a gentle start with strong conceptual clarity.

Topics include:

Linear regression, decision trees
AI vs. ML vs. Deep Learning
Python-based hands-on projects

This Udemy course is best for beginners looking to ease into ML and AI together.

Here is the link to join this AI course on Udemy— Complete A.I. & Machine Learning, Data Science Bootcamp

4. The AI Engineer Course 2026: Complete AI Engineer Bootcamp

Before diving into AI models, you need to know the core tools. This AI course on Udemy will teach you Python programming and libraries like NumPy and Pandas — — essential for every AI developer.

You’ll learn:

Python basics and functions
Data manipulation and visualization
Preparing datasets for machine learning

This course is also best for beginners with zero coding background who want to learn AI from the ground up.

Here is the link to join this AI Engineering course— The AI Engineer Course 2026: Complete AI Engineer Bootcamp

5. The Complete Artificial Intelligence and ChatGPT Course

If you want to use AI tools (rather than build them), this Udemy course is a practical guide to boost productivity with ChatGPT and other AI platforms. No programming skills required.

What’s covered:

Writing, coding, and designing using AI
Prompt engineering basics
Automation using AI tools like Notion AI, Canva AI, etc.

Best for: Creatives, freelancers, and professionals looking to use AI for content creation or daily productivity.

Here is the link to join this Udemy course — The Complete Artificial Intelligence and ChatGPT Course

6. The Beginner’s Guide to AI — — Unity 6 Compatible

If you’re into game development, this online course teaches how to use AI within Unity to build NPC behavior, pathfinding, and decision trees.

Learn how to:

Build intelligent enemies
Implement navigation and movement logic
Simulate decision making in games

Best for: Aspiring game developers who want to implement AI features in games.

Here is the link to join this AI course — — The Beginner’s Guide to AI — — Unity 6 Compatible

7. Intro to AI: A Beginner’s Guide to Artificial Intelligence

Want to explore neural networks and deep learning without overwhelming math? This Udemy course simplifies TensorFlow and Keras to help you start building neural networks fast.

Topics covered:

Deep learning fundamentals
CNNs and image classification
Working with real datasets

Best for: Beginners eager to get hands-on with deep learning frameworks.

Here is the link to join this online course — — Intro to AI: A Beginner’s Guide to Artificial Intelligence

8. ChatGPT/AI for Finance Professionals: Investing & Analysis

This niche AI course shows how to apply AI to financial datasets. You’ll build predictive models, understand time series, and apply neural nets to stock forecasting.

You’ll learn:

Regression, classification, and LSTMs
Real-world datasets and financial indicators
Risk modeling using AI tools

Best for: Finance professionals and data analysts looking to apply AI in their domain.

Here is the link to join this course — — ChatGPT/AI for Finance Professionals: Investing & Analysis

9. The Complete AI Guide: Learn ChatGPT, Generative AI & More

Interested in building smart assistants like Alexa or Google Assistant? This course is a great starting point to understand voice AI and NLP systems.

Covers:

Basics of speech recognition
Natural Language Processing (NLP)
Building chatbots and smart devices

Best for: Curious learners exploring voice-powered AI systems.

Here is the link to join this course — — The Complete AI Guide: Learn ChatGPT, Generative AI & More

10. Generative AI for Beginners: ChatGPT, DALL-E & More

Generative AI is the hottest trend in 2026. This beginner course introduces tools like ChatGPT, DALL-E, and Midjourney — — teaching how to use them creatively and responsibly.

You’ll learn:

Text, image, and code generation
Prompt engineering
Ethics and future of Generative AI

Best for: Beginners who want to explore creative and artistic AI tools.

Here is the link to join this Gen AI course — — Generative AI for Beginners: ChatGPT, DALL-E & More

Conclusion

That’s all about the 10 best Udemy courses to learn AI from scratch in 2026. The world of AI is vast but it doesn’t have to be intimidating. With the right beginner-friendly course, you can build a solid foundation in AI and gradually move toward advanced concepts like deep learning, generative models, or autonomous systems.

Udemy makes this journey approachable with affordable, self-paced courses taught by industry experts. Whether you’re a developer, a non-tech professional, a student, or just curious — — there’s a course here for you.

Pick one and start your AI journey today.

If you got a lot of time and want to save money, Udemy Personal Plan will be perfect for you.

Other AI and Cloud Computing Resources you may like

Thanks for reading this article so far. If you find these Udemy Courses for learning AI from scratch, including tools and libraries then please share with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. — — If you are keen to learn Midjourney and ChatGPT and looking for a free online training course to start with then you can also check out this free ChatGPT, Midjourney, Firefly, Bard, DALL-E, AI Crash course on Udemy. This course is completely free and you just need an Udemy account to join this course. You can also join this course for free with Udemy personal plan.

11 Best ChatGPT Online Courses for Beginners in 2026

Master Conversational AI with Top online Courses on ChatGPT for 2026. Also include best courses on Prompt Engineering…

medium.com

I Tried 20+ Hugging Face Courses on Udemy: Here are Top 5 Which Is Worth it

2026-03-30T07:54:00.000-07:00

Hello guys, In recent years, the field of Natural Language Processing (NLP) has been revolutionized by the advent of transformer-based models like BERT, GPT, and T5.

At the heart of this revolution lies Hugging Face — — a company and an open-source community that has made it significantly easier to work with state-of-the-art transformer models in real-world applications.

Hugging Face’s Transformers library provides a simple and powerful API for accessing over 100,000 pre-trained models for tasks like text classification, question answering, translation, summarization, and more.

With seamless support for TensorFlow, PyTorch, and JAX, it has become the go-to toolkit for developers, data scientists, and researchers working in NLP and beyond.

If you don’t know, Transformers democratizes access to state-of-the-art AI models by providing a simple, unified API. Instead of implementing complex model architectures from scratch, developers can leverage pre-trained models with just a few lines of code.

The library has become the de facto standard for working with transformer models in the Python ecosystem, used by researchers, companies, and developers worldwide for both prototyping and production applications.

By the way, if you are new into Generative AI field then I highly recommend you to checkout this Generative AI for Beginners course on Udemy first.

This is a great course to get a detailed understanding of Generative AI and key concepts like LLM, Embeddings, Prompt Engineering, Fine Tuning with hands-on experience by creating a chatbot.

Why Learn Hugging Face Transformers in 2026?

As we move further into the age of generative AI, learning Hugging Face Transformers is no longer optional — — it’s essential.

Here’s why:

Industry Demand: Companies are actively hiring engineers and data scientists with experience in transformer models.
Cutting-Edge Tools: Hugging Face is a leader in the open-source AI ecosystem, providing tools like 🤗 Transformers, 🤗 Datasets, 🤗 Accelerate, and 🤗 PEFT.
Low-Code AI Development: With the Hugging Face Hub and AutoTrain, even beginners can fine-tune or deploy powerful models without deep ML expertise.
Community & Documentation: Hugging Face has one of the most vibrant communities and user-friendly documentation in machine learning today.

If you’re serious about working with LLMs, fine-tuning models, or building intelligent applications, learning Hugging Face Transformers is definitely a smart investment for 2026 and beyond.

By the way, if you want to become an AI Engineer in 2026 then I highly recommend you to start with The AI Engineer Course 2026: Complete AI Engineer Bootcamp course first. This course provide good overview of all the essential tools, technologies, libraries, and skills you need to become an AI Engineer in 2026.

7 Best Udemy Courses to Learn Hugging Face Transformers in 2026

Without any further ado, here are the top-rated and most up-to-date courses on Udemy to help you master Hugging Face Transformers:

1. Learn Hugging Face Bootcamp

This is a beginner-friendly course that walks you through the basics of using Hugging Face’s Transformers library. With no prior machine learning experience required, you’ll get hands-on with pre-trained models and build real-world NLP applications.

What you’ll learn:

Loading and using pre-trained models (BERT, GPT, etc.)
Performing text classification and sentiment analysis
Basics of tokenization and pipeline APIs
Real-world use cases using Python and Jupyter Notebooks

This course is best for Python developers or data enthusiasts who want to start using powerful language models with minimal setup.

Here is the link to join this course — — Learn Hugging Face Bootcamp

2. Quantizing LLMs with PyTorch and Hugging Face

This Udemy course is ideal for learners who want to understand what’s happening under the hood, this course goes beyond basic usage and dives deep into how transformers work, how they’re trained, and how you can build and fine-tune them from scratch.

Here are key skills you’ll learn:

Gain an intuitive understanding of linear quantization
Learn different linear quantization techniques
Learn from a high-level how 2 & 4-bit quantization works
Learn how to quantize LLMs from Hugging Face

This course is best suited for intermediate and experienced ML engineers or those already familiar with PyTorch.

Here is the link to join this course — — Quantizing LLMs with PyTorch and Hugging Face

3. Learn Hugging Face for Mastering Generative AI with LLMs

This one is a comprehensive Udemy course for developers looking to master Hugging Face and use it in real-world production environments. It focuses on building projects like search engines, summarizers, and LLM-based tools.

Here are key skills you’ll learn:

Full Hugging Face NLP pipeline
Fine-tuning BERT, RoBERTa, and other models
Building LLM-powered applications
Prompt engineering and model evaluation

Perfect for software engineers, data scientists, or NLP practitioners looking to go from beginner to expert.

Here is the link to join this course — — Learn Hugging Face for Mastering Generative AI with LLMs

4. Deep Learning: Natural Language Processing with Transformer

This course is a great fit for those in the TensorFlow/Keras ecosystem. You’ll learn how to load and fine-tune Hugging Face models using TensorFlow instead of PyTorch, with a focus on scalable workflows.

What you’ll learn:

Hugging Face Transformers with TensorFlow backend
Fine-tuning models using Keras API
NLP pipelines using TensorFlow datasets
Model evaluation and deployment

Ideal for TensorFlow developers who want to explore LLMs without switching to PyTorch.

Here is the link to join this course — — Deep Learning: Natural Language Processing with Transformer

5. 2026 Fine Tuning LLM with Hugging Face Transformers for NLP 🤗

This Udemy course is focused entirely on the fine-tuning process, teaching how to adapt pre-trained models to specific tasks like sentiment analysis, classification, or custom domains.

Here is what you’ll learn:

Custom dataset preparation
Fine-tuning and training best practices
Using Trainer API and custom heads
Evaluation and debugging

Recommended for developers who already know how to use pre-trained models and want to make them production-ready.

Here is the link to join this course — — Fine Tuning LLM with Hugging Face Transformers for NLP 🤗

6. Master Streamlit: Build Dashboards with Streamlit & Python

This project-based course is perfect for developers who want to turn models into full applications. It teaches how to wrap Hugging Face models in beautiful web apps using Streamlit.

What you’ll learn:

Building UIs with Streamlit
Integrating Hugging Face Transformers
Creating chatbot interfaces and summarizers
Deployment to the web

Best for developers looking to showcase NLP tools or deploy quick prototypes.

Here is the link to join this course — Master Streamlit: Build Dashboards with Streamlit & Python

7. LLM Engineering with Hugging Face and LangChain

This is one of the best Udemy course for advanced learners who want to build LLM pipelines by combining Hugging Face with LangChain — — great for RAG, agents, and custom LLM workflows.

What you’ll learn:

Retrieval-Augmented Generation (RAG) techniques
Connecting Hugging Face models with LangChain
Creating agents and custom tools
Building end-to-end pipelines

Perfect for AI engineers and backend developers building intelligent applications and LLM agents.

Here is the link to join this course — — LLM Engineering with Hugging Face and LangChain

Conclusion

That’s all about the 7 best Udemy courses to learn Hugging Face library for AI Engineers in 2026. Whether you’re a beginner looking to enter the world of NLP or an experienced developer aiming to build production-ready AI applications, Hugging Face Transformers is the gateway to mastering modern NLP and generative AI.

These Udemy courses are affordable, well-structured, and taught by industry experts — — making them the perfect resources to level up your skills in 2026.

Pick one that matches your learning style and start building smart applications powered by transformers today.

If you got a lot of time and want to save money, Udemy Personal Plan will be perfect for you.

If you found this helpful, don’t forget to share or bookmark it for your AI learning journey!

Other AI, LLM, and Machine Learning resources you may like

Thanks a lot for reading this article so far, if you like these AI and LLM Engineering books then please share with your friends and colleagues. If you have any feedback or questions then please drop a note.

P. S. — — If you are new to Generative AI and Hugging Face transformers then you can also start with Complete Generative AI Course With Langchain and Huggingface course by Kris Nayak. This course provides complete guide to Building, Deploying, and Optimizing Generative AI with Langchain and Huggingface

DevOps Basics - Docker vs Kubernetes vs Podman

2026-03-28T21:42:00.000-07:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

Hello friends, if you are preparing for Tech interviews, you must prepare for container technologies like Docker and Kubernetes, as containers are now used to deploy most apps, including Microservices and monoliths.

One of the most common questions on System Design and Software developer interviews nowadays is the difference between Docker, Kubernetes, and Podman? What they are and when to use them.

In the past, I have talked about system design questions like API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy, and today, I will answer the difference between Docker, Kubernetes, and Podman.

Docker, Kubernetes, and Podman are all popular containerization tools that allow developers and DevOps to package and deploy applications in a consistent and efficient manner.

Docker is a popular containerization platform that allows developers to create, deploy, and run applications in containers.

Docker provides a set of tools and APIs that enable developers to build and manage containerized applications, including Docker Engine, Docker Hub, and Docker Compose.

On the other hand, Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications.

Kubernetes also provides a set of APIs and tools that enable developers to deploy and manage containerized applications at scale, across multiple hosts and environments.

And*, Podman* is a relatively new containerization tool that is similar to Docker, but with a different architecture. Podman does not require a daemon to run containers, and it is compatible with Docker images and registries.

Podman provides a simple command-line interface for creating and managing containers, and it can be used as a drop-in replacement for Docker in many cases.

Now that we have a basic idea of what they are and what they do, let's dive deeper to understand how they work.

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative, Codemia.io, Bugfree.ai and Udemy which have many great System design courses

What is Docker? How does it work?

As I said, Docker is an open-source platform that enables developers to automate the deployment and management of applications within containers.

It provides a way to package an application and its dependencies into a standardized unit called a container, which can be run on any compatible system without worrying about differences in operating systems or underlying infrastructure.

Here are a few important Docker concepts that you, as a Developer or DevOps Engineer, should know :

1. Containerization
Docker utilizes containerization technology to create isolated environments, known as containers, for running applications. Containers are lightweight and encapsulate the application code, runtime, system tools, libraries, and dependencies required to run the application.

This allows applications to run consistently across different environments, ensuring that they behave the same regardless of the underlying system.

2. Docker Images
A Docker image serves as a template for creating containers. It is a read-only snapshot that contains the application code and all the necessary dependencies.

Docker images are created using a Docker file, which is a text file that specifies the steps to build the image. Each step in the Dockerfile represents a layer in the image, allowing for efficient storage and sharing of images.

3. Docker Engine
The Docker Engine is the core component of Docker. It is responsible for building and running containers based on Docker images. The Docker Engine includes a server that manages the containers and a command-line interface (CLI) that allows users to interact with Docker.

4. Docker Registry
Docker images can be stored in a registry, such as Docker Hub or a private registry. A registry is a centralized repository for Docker` images, making it easy to share and distribute images across different systems. Developers can pull pre-built images from registries or push their own custom images for others to use.

5. Container Lifecycle
To run an application, Docker creates a container from an image. Containers are isolated and have their own filesystem, processes, and network interfaces.

They can be started, stopped, paused, and removed as needed. Docker provides a set of commands and APIs to manage the lifecycle of containers, allowing for easy scaling, updates, and monitoring.

6. Container Orchestration
While Docker itself provides container management capabilities, it also works seamlessly with container orchestration platforms like Kubernetes.

These platforms enable the management of large clusters of containers, handling tasks such as load balancing, scaling, and automated deployments across multiple hosts.

Overall, Docker simplifies the process of packaging, distributing, and running applications by utilizing containerization technology. It helps developers achieve consistency, portability, and scalability for their applications, making it a popular choice in modern software development and deployment workflows.

And, if you want to learn more about Docker, I highly recommend you join a good course like Docker & Kubernetes: The Practical Guide by Maximilian Schwarzmuller on Udemy. It's a highly rated, up-to-date, hands-on course to master Docker.

Here is also a nice diagram from ByteByteGo which highlights key components of Docker and how it works:

What is Kubernetes? How does it work?

Both Docker and Kubernetes are like brothers, and they are often referred to together, but they are very different from each other. Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications.

It provides a framework for running and coordinating multiple containers across a cluster of machines, making it easier to manage complex distributed systems.

Here are important Kubernetes or K8 concepts that I think every developer or DevOps should learn and know:

1. Cluster Architecture
Kubernetes operates in a cluster architecture, which consists of a master node and multiple worker nodes. The master node manages the cluster and coordinates the overall operations, while the worker nodes are responsible for running the containers.

2. Pods
The basic unit of deployment in Kubernetes is a pod. A pod is a logical group of one or more containers that are co-located and share the same resources, such as network namespace and storage.

Containers within a pod can communicate with each other using localhost. Pods are treated as ephemeral units and can be easily created, updated, or terminated.

3. Replica Sets and Deployments
Replica Sets define the desired number of identical pod replicas to be running at any given time.

They ensure high availability and scalability by automatically managing and maintaining the desired number of pod instances.

Deployments are a higher-level abstraction that allows you to manage and update Replica Sets declaratively, enabling seamless rolling updates and rollbacks of application versions.

4. Services
Kubernetes Services provide stable network endpoints to connect to a set of pods. They enable load balancing and expose the containers within a pod to other services or external clients.

Services abstract the underlying pod instances, allowing applications to communicate with other components without worrying about their dynamic nature.

5. Labels and Selectors
Kubernetes uses labels and selectors to enable flexible and dynamic grouping and selection of objects. Labels are key-value pairs attached to pods, deployments, services, and other Kubernetes objects.

Selectors are used to filter and match objects based on their labels, allowing for targeted operations and grouping of related resources.

6. Scaling and Auto-Scaling
Kubernetes allows you to scale applications by adjusting the number of pod replicas. Horizontal Pod Autoscaling (HPA) is a feature that automatically scales the number of pod replicas based on resource utilization metrics such as CPU or memory usage.

7. Container Networking
Kubernetes also manages networking between pods and nodes. Each pod gets its own IP address, and containers within a pod can communicate with each other using localhost.

Kubernetes provides network plugins that facilitate container networking and enable communication across pods and clusters.

8. Cluster Management
Kubernetes also offers extensive cluster management capabilities, including rolling updates, secrets management, configuration management, and health monitoring.

It provides a declarative approach to define the desired state of the system, allowing Kubernetes to continuously monitor and reconcile the actual state with the desired state.

9. Container Storage
Kubernetes supports various storage options, including persistent volumes and storage classes. Persistent volumes provide a way to decouple storage from the lifecycle of pods, enabling data persistence and sharing across pods and container restarts.

By abstracting the complexities of managing containers at scale, Kubernetes enables developers to focus on application logic rather than infrastructure management.

It provides a robust and scalable platform for deploying and managing containerized applications, making it a popular choice for building modern, cloud-native systems.

And, if you want to learn more about Kubernetes, I highly recommend you join a good course like Kubernetes for the Absolute Beginners - Hands-on on Udemy. It's a highly rated, up-to-date, hands-on course to master Docker.

Here is a nice diagram that shows different components of K8 or Kubernetes and how they work together:

What is Podman? How does it work?

Now that you already know what Docker and Kubernetes are, it's time to take a look at another popular tool called Podman, which is often seen as an alternative to Docker.

Podman is an open-source container runtime and management tool that provides a command-line interface (CLI) for managing containers.

It aims to be a compatible alternative to Docker, offering a Docker-compatible API and allowing users familiar with Docker to transition easily*. Podman is designed to provide a secure and lightweight container experience.

Here's an overview of how Podman works and important Podman concepts you should know:

1. Container Runtime
Podman serves as a container runtime, which means it can create and run containers. It uses the Open Container Initiative (OCI)-compatible container format, which ensures compatibility with other container runtimes and allows Podman to run OCI-compliant containers.

2. CLI Compatibility
Podman's CLI is designed to be familiar to Docker users. It provides commands similar to Docker CLI, allowing users to manage containers, images, volumes, and networks with ease.

This compatibility makes it easier for developers and system administrators to transition from Docker to Podman without significant changes to their workflows.

3. Rootless Containers
One notable feature of Podman is its support for rootless containers. It allows non-root users to run containers without requiring privileged access.

This enhances security by isolating containers from the host system and reducing the risk of container escapes.

4. Container Management
Podman provides a range of management capabilities, such as creating, starting, stopping, and removing containers. It supports network configuration, allowing containers to communicate with each other and the host system.

Podman also provides options for managing container volumes, environment variables, and resource constraints.

5. Container Images
Like Docker, Podman relies on container images as the basis for creating containers. It can pull and push container images from various container registries, including Docker Hub. Podman can also build images locally using a Dockerfile or import images from other container runtimes.

6. Pod Support
Podman extends beyond individual containers and supports the concept of pods, similar to Kubernetes. Pods are a group of containers that share the same network namespace and resources.

Podman allows users to create and manage pods, enabling more complex deployments and communication patterns between containers.

7. Integration with Orchestration Platforms
While Podman can be used as a standalone container runtime, it can also integrate with container orchestration platforms like Kubernetes. It can act as the container runtime for Kubernetes pods, allowing users to leverage Podman's features and compatibility within a Kubernetes cluster.

8. Security Focus
Podman places a strong emphasis on security. It supports features such as user namespace mapping, which maps container user IDs to non-root user IDs on the host, enhancing container isolation.

Podman also integrates with security-enhancing technologies like SELinux and seccomp profiles to provide additional layers of protection.

Podman aims to provide a seamless transition for Docker users while emphasizing security and lightweight container management.

It offers compatibility, flexibility, and a user-friendly CLI, making it a compelling option for those seeking an alternative container runtime.

What is the difference between Docker, Kubernetes, and Podman?

Here are the key differences between Docker, Kubernetes, and Podman. I have compared them on different points, which are mainly features, and capabilities each of these tools provides like containerization and container management etc.

1. Container Engine
Docker is primarily a container runtime and engine for building, running, and distributing containers. Kubernetes, on the other hand, is an orchestration platform designed for managing containerized applications across a cluster of machines.

Podman is a container runtime and management tool that provides a Docker-compatible CLI and container runtime.

2. Container Format
Docker uses its own container format called Docker containers. Kubernetes can work with multiple container formats, but Docker containers are the most common choice.

Podman, on the other hand, uses the Open Container Initiative (OCI)-compatible container format and can run OCI-compliant containers.

3. Orchestration
Docker has Docker Swarm, its built-in orchestration tool, which allows managing a swarm of Docker nodes for running containers.

Kubernetes, on the other hand, provides advanced orchestration capabilities for managing containerized applications, including scaling, load balancing, automated deployments, and self-healing.

Podman does not have built-in orchestration capabilities like Docker Swarm or Kubernetes, but it can work alongside Kubernetes or other orchestration platforms.

4. Cluster Management
Docker does not have native support for managing container clusters. Kubernetes, on the other hand, is specifically designed for managing container clusters and provides features for scaling, upgrading, monitoring, and managing containerized applications.

Podman does not have native support for managing container clusters but can be used with external tools like Kubernetes or other container orchestration frameworks.

5. Security
For Security comparison, Docker provides basic isolation and security features, but its primary focus is on running single containers. Kubernetes offers advanced security features such as network policies, secrets management, and RBAC.

Podman, on the other hand, focuses on security and provides features like user namespace mapping, seccomp profiles, and SELinux integration for enhanced container security.

6. User Interface
When it comes to comparing UI, Docker provides a user-friendly CLI and a web-based graphical interface (Docker Desktop) for managing containers. Kubernetes has a CLI tool called "kubectl" and a web-based dashboard (Kubernetes Dashboard) for managing containers and clusters.

Podman provides a CLI similar to the Docker CLI and can be used with third-party tools like Cockpit for web-based management.

And, if you like tables, here is a nice table where I have put all the differences between Docker, Kubernetes, and Podman in tabular format:

These are the fundamental differences between Docker, Kubernetes, and Podman, each serving different purposes in the containerization ecosystem.

System Design Interviews Resources:

And, here are curated list of best system design books, online courses, and practice websites which you can check to better prepare for System design interviews. Most of these courses also answer questions I have shared here.

DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
"System Design Interview" by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.
"Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.
LeetCode System Design Tag: LeetCode is a popular platform for technical interview preparation. The System Design tag on LeetCode includes a variety of questions to practice.
"System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.
Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.
YouTube Channels: Check out channels like "Gaurav Sen" and "Tech Dummies" for insightful videos on system design concepts and interview preparation.
ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of the System Design Interview book volumes 1 and 2 and will be updated with volume 3 which is coming soon.
Exponent: A specialized site for interview prep, especially for FAANG companies like Amazon and Google. They also have a great system design course and many other materials that can help you crack FAAN interviews.

image_credit - ByteByteGo

That's all about the difference between Docker, Kubernetes, and Podman. In summary, Docker is a popular containerization platform for creating and managing containers, Kubernetes is a container orchestration platform for managing containerized applications at scale, and Podman is a containerization tool with a different architecture that can be used as a drop-in replacement for Docker in many cases.

Each of these tools serves a different purpose, and they can all be used together to provide a comprehensive containerization solution for developers, but more importantly, every Developer and DevOps should be aware of these tools.

The Software Engineer's Reading List for 2026 (10 Books That Matter)

2026-03-28T02:49:00.000-07:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

Credit - ByteByteGo - https://bit.ly/3P3eqMN

Hello Devs, if you have worked as a Software Engineer, Developer, or Programmer, you may know that, as software engineers, continuous learning is not just a goal—it's a necessity.

From one task to the next, from one project to the next, there is always learning required. Many times you need to learn a new programming language or framework, or library, or coding and designing.

And, when it comes to learning, nothing beats a book.

Whether you're looking to refine your coding practices, master system design, or gain a deeper understanding of software architecture, the right books can offer insights and techniques to elevate your skills.

I know that we learn from our experience, and books are a great way to learn from other people's experiences.

There is a limit to how much you can learn from your own experience, but if you start learning from other folks' experiences, then there is no limit.

And, books give a glimpse of how experts think, what understanding they have of certain topics that matter most for software engineers and developers.

In the last few articles, I have shared many popular system design questions like API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy as well as 50 system design problems and today I am going to share the 10 books you can read to become a better software engineer.

This article features ten essential books every software engineer should read, divided into five categories: General Advice, Coding, Software Architecture, Design Patterns, and Data Structures & Algorithms.

So what are we waiting for? Let's start

10 Books Every Software Engineer and Developer Must Read

Without any further ado, here are the best books any Software engineer, developer, or programmer can read.

We will start with general advice for programmers and then finish it on Data Structures and Algorithms, one topic that separates amateurs from professionals in the programming field.

General Advice

The Pragmatic Programmer This classic by Andrew Hunt and David Thomas provides actionable advice for software developers, from debugging techniques to career growth. It emphasizes the importance of being adaptable and continuously refining your craft.
Code Complete (2nd Edition) Written by Steve McConnell, this book is often hailed as a comprehensive guide to software construction.

It provides proven practices for writing robust, maintainable code and improving your software craftsmanship. This book was first recommended to me by our tech lead, who had a tradition of giving this book to every new joiner in the company.

Coding

Now, let's see a few coding books that every software engineer should read

Clean Code
By Robert C. Martin ("Uncle Bob"), this book is a manifesto for writing readable, efficient, and maintainable code. It provides practical examples of bad code versus clean code and teaches you the mindset of a skilled programmer.
Refactoring: Improving the Design of Existing Code
This book by Martin Fowler is essential for anyone looking to improve their existing codebase without introducing new bugs. It's a step-by-step guide to transforming bad code into good code while preserving functionality.

Software Architecture

Designing Data-Intensive Applications
By Martin Kleppmann, this book dives deep into the systems that power modern software applications. It's an indispensable resource for understanding distributed systems, data pipelines, and scalability.
System Design Interview (Volumes 1 & 2)
Designed to prepare you for system design interviews, these books by Alex Xu break down complex systems into simple, digestible components. They're packed with real-world examples and diagrams to help you master system design.

Design Patterns

Design Patterns: Elements of Reusable Object-Oriented Software
This seminal work by Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides (the "Gang of Four") introduces 23 foundational design patterns. It's a must-read for understanding object-oriented programming and software design.
Domain-Driven Design: Tackling Complexity in the Heart of Software
By Eric Evans, this book explores techniques to handle complex business domains in software development. It emphasizes collaboration between developers and domain experts to create intuitive, effective systems.

Data Structures & Algorithms

Introduction to Algorithms
Known as the "CLRS book," this comprehensive guide covers a wide range of algorithms and data structures, complete with mathematical rigor. It's an essential resource for both beginners and seasoned developers.
Cracking the Coding Interview
By Gayle Laakmann McDowell, this book is the ultimate resource for technical interviews. It provides 189 programming questions and solutions, along with strategies to tackle them effectively.

Why These Programming and Development Books Matter?

This is a good question: why should you read these books? There are better things you can do, like watching Squid Games season 2 on Netflix or binge-watching YouTube videos, so why should one read these books?

Well, these ten books collectively address the most critical aspects of software engineering.

From honing your coding skills and understanding architectural design to mastering data structures and algorithms, they prepare you for real-world challenges and interviews alike.

Just reading these books will expand your knowledge base, and even if you don't get 100%, you will be a much better engineer than without reading these books.

If you ask me, I have read most of them, not page to page, but most of it, and I can say that every time I read a book, I come up with more knowledge and wisdom, even on topics that I thought I knew very well.

If you want to just read one book, start with Clean Code, one of my favorite books on coding. I learned a lot about coding as an art from this book.

It's the one that takes you from HelloWorld programmer to a professional, well, at least it made that impact for me.

How to Get Started? Which Book Should You Read First

This is a difficult part, especially if you are presented with a list of 10 books.

I would suggest starting by identifying the areas where you want to improve.

If you're aiming for cleaner code, dive into Clean Code or Refactoring: Improving the Design of Existing Code.

Preparing for interviews? Focus on "Cracking the Coding Interview" and System Design Interview (Volumes 1 & 2)

If you're venturing into software architecture, Design Patterns: Elements of Reusable Object-Oriented Software is a must-read.

Remember, each of these books represents a treasure trove of knowledge that can transform your approach to software engineering. So pick one today and start your journey toward mastery!

All the best with your learning journey !!

Bonus

As promised, here is the bonus for you, a free book. I just found a new free book to learn Distributed System Design, you can also read it here on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

image_credit --- twitter

The 5 Most In-Demand Programming Skills to Learn in 2026

2026-03-27T08:26:00.000-07:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - Exponent

Hello devs, if you have been doing programming and software development, then you know that there is only one constant in our field, and that is "Change".

We always need to learn new tools, technologies, frameworks, and skills to do our job, and there is no end to it. If you don't learn, you will be left behind with others; that's why I always look for new skills to learn.

In this article, I am going to share 5 skills programmers and developers can learn in 2026 to become better at their job and also become more efficient.

In the past, I talked about difference between API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy, which you guys liked a lot and in this article I am going to share top five developer skills that are set to take center stage in 2026.

P.S. Keep reading until the end. I have a bonus for you.

These skills include both new and old but essential skills like prompt engineering, coding, cloud computing realms, system design, and Python; these skills are in demand and essential for any software developer.

Whether you're an experienced developer looking to upgrade yourself or an intermediate developer who wants to enhance their profile, these skills will certainly help you.

5 Skills Software Engineers Should Learn in 2026

In the ever-evolving landscape of technology, staying ahead of the curve is essential for developers seeking to thrive in 2026 and beyond.

As we navigate through the dynamic realms of software development, certain skills have emerged as indispensable for the modern developer, and that's what you are going to learn in this article.

Let's deep dive into the top five developer skills that are poised to make a significant impact in 2026.

1. System Design

In 2026, developers need to go beyond traditional coding practices and embrace modern system design principles. This involves understanding distributed systems, microservices architecture, and designing scalable and resilient applications.

Developers who can navigate complexities in system design are better equipped to create robust solutions that can handle the demands of a rapidly evolving technological landscape.

If you want to learn System Design in depth, then you can also check out sites like ByteByteGo, Design Guru, Exponent, Educative Bugfree.ai and Udemy which have many great System design courses

If you need more resources, then here is a list of System design books, courses, and websites to learn and master Software design and architecture in 2026.

2. Prompt Engineering

In this era of AI tools, Software development is not untouched, and more and more AI tools are coming to help you with Coding, debugging, and testing, but you need prompt engineering to make effective use of these tools.

In other words, Prompt engineering has become a crucial skill for developers aiming to deliver high-quality products quickly.

This involves not only writing efficient and concise code but also adopting agile methodologies and tools to streamline the entire development process.

Developers proficient in prompt engineering can rapidly respond to changing requirements, ensuring their software remains adaptable and resilient in the face of evolving market demands.

If you need a resource to learn ChatGPT and Prompt Engineering, then I suggest you see ChatGPT Prompt Engineering for Developers course on Coursera.

If you need more options, then you can also see these ChatGPT and Prompt Engineering courses to learn more.

3. Coding

While coding might seem like an obvious skill, its significance cannot be overstated. Mastery in coding goes beyond writing functional programs; it involves writing clean, maintainable, and scalable code.

Developers should focus on enhancing their proficiency in programming languages, understanding algorithms, and implementing best practices.

A solid foundation in coding forms the bedrock for success in any development endeavor. And, if you need a resource, you can check out The Complete JavaScript Course 2026: Build Real Projects to start with.

If you need more choices, you can also check out these Programming and Coding courses

4. Cloud Computing

Cloud computing has transcended from being a buzzword to an essential skill for developers. With the increasing reliance on cloud services, developers must be well-versed in deploying, managing, and optimizing applications in cloud environments.

Platforms like AWS, Azure, and Google Cloud are integral to modern development, and developers proficient in cloud computing can create scalable and cost-effective solutions.

And, if you need resources, you can see these articles where you can find highly recommended resources to learn Cloud Computing

And, if you need more choices, you can also see this article where you can find highly recommended AWS Fundamentals Specialization on Coursera. This program is created by AWS itself.

5. Python

Python continues to assert its dominance as a versatile and powerful programming language. From web development to data science, machine learning, and artificial intelligence, Python is at the forefront of innovation.

Developers in 2026 should invest in mastering Python, as it not only facilitates rapid development but also provides a gateway to a plethora of cutting-edge technologies shaping the future of the industry.

If you want to learn and master Python in 2026, you can start with this Python course 100 Days of Code: The Complete Python Pro Bootcamp for 2026, which I am also using to learn Python nowadays.

If you need more resources, you can also see these Python books, courses, and websites to learn Python in depth.

That's all about the top 5 developer skills you can learn in 2026. In conclusion, the top developer skills for 2026 reflect the industry's demand for agility, adaptability, and technical excellence.

Whether you are a seasoned developer or just starting your coding journey, honing these skills will undoubtedly position you as a valuable asset in the ever-evolving world of software development.

Embrace the challenges, stay curious, and embark on a journey of continuous learning to thrive in the dynamic landscape of 2026 and beyond.

Bonus

As promised, here is the bonus for you, a free book which you can read to learn Distributed System Design. You can either download the Free PDF or read online on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

And let me know in the comments which skills you are learning in 2026? I am always eager to learn skills that can enhance my profile as a software developer.

Thank you

10 Real Microservices Architecture Challenges Every Senior Engineer Must Know

2026-03-26T06:59:00.000-07:00

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

image_credit - ByteByteGo

Hello friends, if you are preparing for system design interview then you must also prepare for Microservices architecture. It's favorite architecture of many interviewers and it provide a lot of material to grill you.

There is no doubt that Microservices architecture has revolutionized software development by breaking down monolithic applications into smaller, loosely coupled services.

In the past, I have shared several system design interview articles like API Gateway vs load balancer, Forward Proxy vs Reverse Proxy as well common System Design problems and in this article we will discuss about the challenges of Microservices architecture.

It's also one of the essential System design topics or concepts for programmers to know.

While Microservices approach promises increased scalability, flexibility, and faster development cycles but it comes with its own set of challenges which is very important for a developer to know, not just know but to solve them efficiently.

While there are many articles which talk about Microservices best practices, there are few which put light on what benefits they offer and what challenges they solve.

In this article, we will explore the ten key challenges that developers face when working with microservices and learn effective strategies to overcome them.

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative and Udemy which have many great System design courses

Also a solid knowledge of various Microservices patterns like Service Discovery, CQRS, and Saga goes a long way in solving many of the challenges we are going to discuss in this article, on that note, here is a nice diagram from DesignGuru.io on how the service discovery work in Microservices, we will use this pattern later in the article

10 Challenges of Microservices Development and Solutions

Here is a list of key challenges one can face while creating applications using Microservices architecture

1. Service Communication Challenges

If you have worked in a real world Microservice architecture then you may know that Microservices rely heavily on inter-service communication, which can become a challenge as the number of services grows.

With each service having its own API and protocols, managing communication becomes complex.

To deal with this, adopt communication patterns like REST, message queues, and event-driven architecture. Also, consider using API gateways to centralize communication logic and handle cross-cutting concerns.

2. Data Management Challenges

Data management across microservices can be intricate due to the decentralized nature of the architecture. Inconsistent data models and maintaining data consistency pose difficulties.

In order to solve this problem, you can implement a polyglot persistence strategy, using databases that suit the specific needs of each service.

You should also leverage techniques like event sourcing andCQRS (Command Query Responsibility Segregation)to maintain data integrity and separation of read and write operations.

3. Distributed Tracing and Monitoring Challenge

Monitoring and debugging microservice applications becomes really challenging as requests span multiple services. Traditional monitoring tools may not provide the required visibility.

In order to solve this proble,m you should integrate distributed tracing systems like Jaeger or Zipkin to track requests across services.

You can also use centralized logging and monitoring solutions to aggregate and analyze logs and metrics from various services, aiding in early issue detection.

For developers, debugging issues in Microservices is one of the biggest challenges to deal with, and knowing about tracing systems like Zipkin really works.

4. Service Orchestration and Choreography Challenges

Microservices can be orchestrated centrally or choreographed in a decentralized manner. Both approaches have their challenges.

Orchestrating services might lead to a single point of failure, while choreography can result in increased complexity and difficulty in tracking the flow.

In this situation, you should strive for a balance, employing orchestration for critical workflows and choreography for services that can operate independently.

5. Deployment and DevOps Challenges

The deployment of Microservices involves managing multiple service instances and ensuring compatibility across different environments. It's almost impossible to deploy a microservice using the traditional way.

Containerization using tools like Docker and orchestration using Kubernetes can help standardize deployment processes, and in fact, they are a must if you want to have peace of mind.

You should also embrace DevOps practices and automate deployment pipelines to ensure consistency and rapid deployment of microservices.

6. Testing across Services Challenges

Testing Microservices is not easy at all; it requires comprehensive strategies due to the intricate nature of their interactions.

Traditional unit testing might not be sufficient.

To solve this problem, you can incorporate integration testing, contract testing, and end-to-end testing to validate service interactions and data flow.

You should also implement a robust CI/CD pipeline that automates testing across the entire microservices ecosystem.

7. Security and Access Control Challenges

Microservices can expose numerous endpoints, increasing the potential attack surface. Most of the time, you will not even be aware of this, but don't worry, almost all big organizations have a big security team with fat pay to hassle you.

On your part, you should ensure security across services, managing authentication and authorization, and securing data in transit, which pose significant challenges.

Adopt a zero-trust security model, implement API security standards like OAuth2 and JWT (JSON Web Tokens), and employ API gateways with strong access control mechanisms.

credit --- superTokens

8. Scalability and Resource Allocation

Scalability is a central promise of microservices and one of the main drivers for many companies to ditch monoliths in favor of Microservices, but it requires careful planning.

Some services might experience heavier loads than others, leading to resource allocation challenges.

You should utilize container orchestration platforms and tools like K8 to dynamically allocate resources based on demand.

You can also implement auto-scaling based on metrics like CPU usage or request rate to ensure optimal resource utilization.

9. Versioning and Compatibility Challenges

As Microservices evolve independently, maintaining backward and forward compatibility becomes vital.

Incompatible changes can disrupt the entire system.

As an experienced developer or tech lead, you should implement versioning for APIs, both at the code level and in communication protocols.

You can also utilize semantic versioning to clearly communicate compatibility expectations. Gradually phase out older versions while providing adequate support and documentation for migrations.

10. Organizational Complexity and Communication Challenges

Microservices architecture can mirror an organization's structure, leading to challenges in communication and collaboration, for example, different teams managing different microservices.

It's important that Cross-functional teams working on different services need to align their efforts.

As an experienced hand, you should foster a culture of communication and collaboration through regular meetings, shared documentation, and tools that facilitate information exchange.

Top 10 System Design Interviews Resources for 2026

And, here is the curated list of best system design books, online courses, and practice websites which you can check to better prepare for System design interviews. Most of these courses also answer questions I have shared here.

ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of the System Design Interview book volumes 1 and 2 and will be updated with volume 3, which is coming soon.
Exponent: A specialized site for interview prep, especially for FAANG companies like Amazon and Google. They also have a great system design course and many other materials that can help you crack FAANG interviews.
DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
LeetCode for System Design - Bugfree.ai: This is a popular platform for technical interview preparation. The System Design tag includes a variety of questions to practice.
"System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.
Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.
High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.
YouTube Channels: Check out channels like "Gaurav Sen" and "Tech Dummies" for insightful videos on system design concepts and interview preparation.
"System Design Interview" by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.
"Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.

And, here is a nice system design interview cheat sheet to quickly revise essential System design concepts:

image_credit - tryExponent

Conclusion

That's all about the Microservices architecture challenges and how to deal with them. Microservices architecture offers remarkable benefits in terms of scalability, flexibility, and faster development.

However, these advantages are accompanied by a unique set of challenges that developers must navigate effectively.

By adopting best practices in service communication, data management, monitoring, testing, security, and more, teams can overcome these challenges and unlock the full potential of microservices.

As the landscape of software development continues to evolve, addressing these challenges will remain essential for successful microservices implementation

While I write this article for system design interview preparation, its equally valuable to experienced developers who are working with Microservices and want more control and better organization.

All the best with Microservices development !!

Bonus\
As promised, here is the bonus for you, a free book. I just found a new free book to learn Distributed System Design, you can also read it here on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

5 Best Artificial Intelligence Courses to Take on Frontend Masters in 2026

2026-03-25T08:11:00.000-07:00

Hello guys, if you are a Software developer then let me tell you an uncomfortable truth: most developers think AI is someone else’s problem. It’s not. It’s your problem. And it’s urgent.

Every developer who hasn’t learned AI in 2026 is betting that their career will continue without it. That’s not a bet — that’s denial.

Frontend Masters isn’t your typical online learning platform. It’s different because it’s taught by people like Scott Moss (former Netflix engineer), Will Sentance (creator of some of the best developer education), and Maximiliano Firtman (web pioneer).

These aren’t content creators teaching theory. These are engineers shipping AI in production.

The courses on Frontend Masters don’t teach you AI academia. They teach you how to actually build things with AI. How to integrate LLMs into your apps. How to deploy agents. How to think about AI architecture. That’s what matters in 2026.

Let me walk you through the five best AI courses on Frontend Masters which you watch to improve your AI knowledge and gain some hands-on AI skills in 2026.

AI Agents | LLMs, Function Calling, and Dahl-E Image Generation

Create your own chat-based AI agent with custom function calling, LLMs, and Dall-E image generation.

frontendmasters.com

5 Best Frontend Masters Courses to learn Artificial Intelligence and Agentic AI in 2026

Without any further ado, here are the best frontend masters courses you can join in 2026 to learn both Artificial Intelligence as well as Agentic AI from scratch.

1. Hard Parts of AI: Neural Networks by Will Sentance

Will Sentance has this gift of making complex concepts feel obvious in hindsight. This course explores the full mental models of AI prediction and LLM model development — from the theory of how neural networks work to actually building predictive systems.

What You’ll Learn:

How AI prediction fundamentally works
Building mental models of neural networks
How LLMs are developed and function
Real-world predictive systems (like DoorDash refund automation)
The intuition behind machine learning
Why predictions work the way they do
Deploying ML models to production

Why It Works: Most developers learn AI and still don’t understand it. Will teaches you to understand. You’ll know why neural networks work, not just that they do. This knowledge compounds. Every AI project after this becomes clearer.

The course uses real examples like automated refund request systems, making abstract concepts concrete and immediately applicable.

Here is the link to join this course — Hard Parts of AI: Neural Networks

Best For: Developers who want to truly understand AI at a fundamental level before building with it. If you want the “why,” this is it.

Time Commitment: 8–10 hours of focused learning

Student Reviews: “The course made some of the concepts in the field of AI less intimidating while building great mental models for understanding.”

2. Build AI Agents from Scratch by Scott Moss

This is where theory meets reality. Scott Moss teaches you to build actual AI agents — systems that can think, decide, and take action — from the ground up.

What You’ll Learn:

Large Language Models (LLMs) fundamentals
Building conversational agents and transactional agents
Function calling and custom tool integration
Integrating Claude, ChatGPT, and other LLMs
Building agents that read from APIs (like Reddit)
Generating images with DALL-E
Real-world agent architecture patterns

Why It Works: Scott believes in learning by building. You’ll create an agent that reads from Reddit, generates images, and provides random dad jokes. Sounds simple? Wait until you understand the architecture behind it.

This course is hands-on, direct, and focused on what actually works in production. Scott doesn’t waste time on theory you don’t need.

Here is the link to join this course — Build AI Agents from Scratch

Best For: Developers who want to build AI agents immediately. If you want to ship something, start here.

Prerequisites: JavaScript knowledge and familiarity with APIs

Student Feedback: “The course truly opened my mind to what’s possible when building intelligent systems. Scott is great — he has this super relaxed, but brilliant mad scientist vibe that makes learning feel comfortable and enjoyable.”

3. AI Agents: From Prototype to Production by Scott Moss

You built an agent. Now make it production-ready. This advanced course takes everything from the fundamentals course and applies it to real-world deployment challenges.

What You’ll Learn:

Taking prototype agents to production
Memory management and context handling
Evals and human-in-the-loop systems
Retrieval Augmented Generation (RAG)
Production guardrails and safety
Monitoring and debugging AI agents
Scaling agents for reliability
Real-world deployment patterns

Why It Works: Building an agent locally is fun. Making it handle edge cases, maintain memory across sessions, and operate reliably in production is hard. This course teaches you that hard part.

Scott’s experience at Netflix and his daily work with AI in production means you’re learning what actually works when real users depend on your systems.

Best For: Developers who’ve built prototype agents and want to ship them professionally. If your agent will handle real traffic, you need this.

Prerequisites: Complete “Build AI Agents from Scratch” first

Student Testimonial: “This course builds on the fundamentals and prepares AI apps for actual production deployment.”

Here is the link to join this course — AI Agents: From Prototype to Production

4. Build AI-Powered Apps with OpenAI and Node.js by Scott Moss

This course dives deep into AI without building a UI. Pure AI integration with Node.js and OpenAI. You’ll learn how to leverage AI techniques in applications at the backend level.

What You’ll Learn:

OpenAI API integration
Building AI applications with Node.js
Semantic search and embeddings
Function calling and tool use
Creating AI chat interfaces
Document question-answering systems
Image generation with APIs
Building production AI systems

Why It Works: Most AI courses mix in frontend complexity. This focuses purely on AI — what you can do with LLMs, how to architect AI flows, how to build useful systems. No UI distractions.

The course includes real code examples that you can reference, with detailed explanations for every line. You’ll understand not just what you’re doing but why.

Best For: Backend developers wanting to integrate AI into their applications. Node.js developers building AI systems. Anyone wanting AI expertise without frontend complexity.

Student Experience: “Scott’s teaching style is mostly coding. He dives deep, gets practical, and doesn’t waste time on unnecessary theory. Perfect for learning by doing.”

Here is the link to join this course — Build AI-Powered Apps with OpenAI and Node.js

5. First Look: ChatGPT API for Web Developers by Maximiliano Firtman

Maximiliano teaches you how ChatGPT and modern LLMs change web development. From chatbots to plugins to content generation, this course shows practical ways to integrate AI into web applications.

What You’ll Learn:

Integrating ChatGPT into web apps
Building chatbots and conversational interfaces
Using AI for content creation and personalization
Language translation with LLMs
Plugins and API integrations
AI in web development workflows
ChatGPT plugins architecture
Practical web + AI examples

Why It Works: Maximiliano approaches AI from a web developer’s perspective. How do I use this in my next project? How does this change my workflow? How do I integrate it into existing applications?

Real examples include building plugins, creating personalized content, and using AI for customer interactions.

Here is the link to join this course — First Look: ChatGPT API for Web Developers

Best For: Web developers wanting to understand how AI fits into web development. Frontend developers integrating AI features. Anyone building customer-facing AI applications.

Time Commitment: 6–8 hours

Practical Value: Immediate application in web projects

My Recommended Learning Path

There are three ways you can take these courses:

Path 1: I Want to Understand AI Fundamentally (2–3 months)

Week 1–2: AI Fundamentals for Software Engineers — Build mental models
Week 3–4: First Look: ChatGPT API for Web Developers — See practical integration
Week 5–6: Build AI Agents from Scratch — Apply your knowledge

Path 2: I Want to Build AI Applications (3–4 months)

Week 1–2: Build AI Agents from Scratch — Get building immediately
Week 3–5: Build AI-Powered Apps with OpenAI and Node.js — Deepen your integration skills
Week 6–8: AI Agents: From Prototype to Production — Ship it for real

Path 3: The Complete AI Mastery (4–5 months) Take all five courses in order. You’ll have comprehensive knowledge from fundamentals to shipping production systems.

Production AI Apps | Evals, RAG, Human in the Loop

Make your AI apps production ready with evals, human-in-the-loop guardrails, memory management, and Retrieval Augmented…

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Why Frontend Masters for Learning AI?

You must be wondering why frontend masters for learning AI? Isn’t Frontend Masters is specialized on frontend development courses? well, that’s true but in the recent years they have expanded their courses and brought the same quality on teaching other fields including AI.

Here are a couple of reasons why I recommend Frontend Masters courses to learn AI in 2026:

Taught by practitioners — Scott Moss, Will Sentance, Maximiliano. Real engineers shipping real systems.
Production-focused — Not theory. What works in production. What you’ll actually do.
Hands-on learning — Build things. Run code. Ship projects.
Updated continuously — AI moves fast. These courses stay current for 2026.
Community of learners — Lifetime access, course forums, peer support.
Comprehensive coverage — From fundamentals to production deployment.

All these reasons make Frontend Masters a great place to learn AI, particularly Agentic AI in 2026.

Get Started Today

AI adoption is accelerating. The window where you can learn AI and gain an advantage is closing. In 2026, knowing AI isn’t special anymore — not knowing it is a liability.

Frontend Masters gives you the education you need to stay ahead.

Join Frontend Masters today for annual membership (~$390/year) and get unlimited access to these AI courses plus 200+ others. It’s the best investment you can make in your 2026 career.

Your AI education starts now. Pick a path. Commit to it. In a few months, you’ll be building AI applications that your competition only dreams about.

The future is AI. Make sure you’re building it.

Start your AI journey on Frontend Masters →

Pricing

Unlimited learning with 250+ courses, live workshops, and mobile apps to level up anywhere Elijah Manor Austin Akers…

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Happy learning!

Other Frontend Masters Resources you may like to read

Pricing

Unlimited learning with 250+ courses, live workshops, and mobile apps to level up anywhere Elijah Manor Austin Akers…

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Is Frontend Masters Good Place to Learn TypeScript in 2026?

2026-03-24T07:52:00.000-07:00

image_Credit — Frontend Masters

Hello folks, are you looking for a high-quality TypeScript course to level up your TypeScript or just want to learn TypeScript from scratch then you have come to the right place.

Earlier, I have shared best TypeScript courses and today, I am going to review one of those, the TypeScript 5+ Fundamentals” by Mike North from Frontend Masters, one of my favorite place to learn everything about web development, including TypeScript.

With the rapid evolution of web development technologies, staying updated with the latest tools and frameworks is essential for developers seeking to enhance their skill set.

TypeScript has emerged as a powerful superset of JavaScript, offering static typing, enhanced tooling, and improved developer productivity.

Press enter or click to view image in full size

Frontend Masters, a leading online learning platform, offers a comprehensive TypeScript course titled “TypeScript 5+ Fundamentals” by Mike North.

In this review, we’ll delve into the course content, structure, and learning outcomes to determine whether it’s worth investing your time and resources.

By the way, I have an exciting news to share with you, Frontend Masters is offering $100 off their yearly membership during their Knowledge Quest Sale.

This is your chance to access over 200+ premium courses, guided learning paths, and new platform features, all at a fraction of the cost.

Whether you want to master JavaScript, React, or DevOps, now’s the time to join and level up your skills. Don’t miss out — the sale ends on 18th September!

👉 Join today and save $100 on your yearly membership!

Frontend Masters Knowledge Quest Sale

Celebrating new powerful features that empower you to explore your software development journey!

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I Frontend Masters Good Place to Learn TypeScript? It their TypeScript course Really Worth it?

We will review the TypeScript course from Frontend Masters on Instructor quality, course quality, and course structure to find out whether its worth of your time and money or not because its not free, you would need a Frontend Master subscription to watch the course.

Instructor Expertise

This course is created by Mike North, a Principal Staff Engineer and Tech Lead of Developer Platform at Stripe, one of the leading payment company in the worth.

His role includes defining the company’s public API semantics and types, as well as driving many large TypeScript projects like the Node.js Stripe SDK Stripe Shell, and Stripe Workbench.

This means you will be learning from a real expert who have delivered a real-world application used by millions of people and can process billions of transactions. This is huge !!

Prior to working at Stripe, Mike was a Senior Staff Engineer at LinkedIn, the CTO of Levanto Financial and the UI Architect of Yahoo’s Ads & Data division.

As part of his ongoing work to improve the JavaScript ecosystem, Mike is also regular contributor and maintainer of a wide range of open source libraries. His areas of focus are TypeScript, Ember.js, CLIs and Progressive Web Applications.

TAlking about his teach style, he is very clear and you will learn and remember a lot of stuff. Just watch the preview lesson, its really good and you will know how well Mike teaches.

You can learn more about Mike here

Course Curriculum and Structure

The “TypeScript 5+ Fundamentals” course on Frontend Masters is a meticulously crafted learning path designed to equip developers with the essential knowledge and skills required to harness the power of TypeScript effectively.

Taught by Mike North, a seasoned developer with experience at Stripe, the course covers a wide range of topics, including variable typing, function signatures, generics, interfaces, classes, and more.

Key Learning Paths and Topics:

TypeScript Fundamentals: The course begins with an introduction to TypeScript, highlighting its importance in reducing bugs and improving code maintainability. Topics such as variable typing, type inference, and type annotations are covered in depth, providing learners with a solid foundation in TypeScript fundamentals.
Objects, Arrays, and Tuples: Participants learn how to work with complex data structures in TypeScript, including objects, arrays, and tuples. Concepts such as index signatures, read-only arrays, and structural vs. nominal typing are elucidated, empowering developers to manipulate data effectively.
Union and Intersection Types: The course delves into advanced type system features such as union and intersection types, exploring their applications in modeling complex data scenarios. Participants gain insights into handling conditional logic, type guards, and discriminated unions, enabling them to write more robust and type-safe code.
Interfaces and Type Aliases: Learners are introduced to TypeScript’s interface and type alias constructs, essential for defining custom data shapes and contracts. Through hands-on exercises and real-world examples, developers learn how to leverage interfaces for code organization, type abstraction, and code reuse.
Type Queries, Callables, and Constructables: The course explores advanced TypeScript concepts, including type queries, callable types, and constructable types. Participants gain a deeper understanding of type system introspection, function signatures, and class definitions, enhancing their proficiency in TypeScript development.
Generics: The course concludes with an in-depth exploration of generics, a powerful feature of TypeScript for creating reusable and type-safe components. Developers learn when and how to apply generics effectively, solving common programming challenges and enhancing code flexibility and scalability.

You can see that the course is quite comprehensive, its also visible from looking at the table of content which is quite detailed

Introduction and Basics

Press enter or click to view image in full size

Objects, Arrays and Tuples

Press enter or click to view image in full size

Interface

Press enter or click to view image in full size

and finally, Classes and Type Guards

Press enter or click to view image in full size

Course Structure and Delivery:

The course is structured in a logical and progressive manner, with each module building upon the concepts covered in previous sections. Mike North’s teaching style is engaging, clear, and concise, making complex topics accessible to learners of all levels.

Hands-on exercises, code demonstrations, and real-world examples reinforce theoretical concepts, enabling participants to apply their newfound knowledge in practical scenarios.

Pros:

Comprehensive Coverage: The course covers a wide range of TypeScript topics, from basic syntax to advanced type system features, providing learners with a comprehensive understanding of the language.
Hands-On Learning: Practical exercises and code demonstrations enhance the learning experience, allowing participants to gain practical experience and reinforce theoretical concepts.
Experienced Instructor: Mike North’s expertise and industry experience shine through in his teaching, making the course engaging and informative for learners.
Structured Curriculum: The course follows a structured curriculum, guiding learners through a logical progression of topics and ensuring a systematic understanding of TypeScript fundamentals.

In short, one of the great course to learn TypeScript in depth.

Here is the link to join this course — “TypeScript 5+ Fundamentals”

Cons

Nothing is perfect and there are room for improvement everywhere, here are things which can cause few concerns to some people looking to join this course:

Advanced Topics: Some advanced topics may require additional practice and exploration to fully grasp, especially for learners new to TypeScript or static typing concepts.
Limited Interaction: While the course offers valuable content, interaction with the instructor and fellow participants is limited to pre-recorded videos, potentially hindering collaborative learning opportunities.

Conclusion

Overall, the “TypeScript 5+ Fundamentals” course on Frontend Masters offers immense value for developers looking to enhance their TypeScript skills.

With its comprehensive coverage, hands-on learning approach, and experienced instructor, the course provides a solid foundation in TypeScript development, empowering participants to write more robust, maintainable, and scalable code.

Whether you’re a seasoned developer seeking to level up your skills or a beginner looking to dive into TypeScript, this course is definitely worth considering as part of your learning journey.

All the best with your TypeScript journey!!

If you want to do just one thing, go and join this course on Frontend Masters

Learn the Fundamentals of TypeScript From Basic Typing to Advanced - Type Aliases…

TypeScript adds a powerful type system to JavaScript, adding type aliases, union/intersection types, and generics…

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Other Frontend Masters Articles you may like to read

P. S. — If you are keen to level up your frontend skills then joining frontend master can be a great first step as they have awesome courses to learn valuable frontend skills. They are also offering $100 discount on their Frontend Master Knowledge quest sale, so, if you want to join now is the best time.

👉 Join today and save $100 on your yearly membership!

Frontend Masters Knowledge Quest Sale

Celebrating new powerful features that empower you to explore your software development journey!

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Database Sharding 101: The One Topic You Must Nail in Every System Design Interview

2026-03-18T21:23:00.000-07:00

Hello friends, in this data driven world, the ability to efficiently handle vast amounts of data is crucial for businesses and organizations. Traditional monolithic databases often struggle to keep pace with the demands of modern applications and services and become performance bottleneck. This is where database sharding comes into play, offering a powerful solution for horizontally scaling your data. If you don't know what is Sharding? Well, Sharding is a database architecture technique that involves partitioning a large database into smaller, more manageable pieces, called "shards," which are distributed across multiple servers.

Each shard contains a subset of the data, and together they form the complete dataset. This approach enhances performance and scalability by distributing the workload, reducing latency, and enabling parallel processing.

Review - Is Educative Unlimited Plan Really Worth It in 2026?

2026-03-16T21:38:00.000-07:00

With the ever-growing demand for software development skills, online learning platforms like Educative.io have become popular choices for developers looking to upskill efficiently.

Among its offerings, the Educative Unlimited Subscription is a widely discussed plan that grants access to hundreds of courses, including popular ones like “Grokking the Coding Interview” and “ Grokking Modern System Design for Software Engineers & Managers

But is the Educative Unlimited Subscription worth it in 2026? In this article, we’ll analyze the platform’s strengths, drawbacks, pricing, course quality, and community feedback to help you decide if it’s the right investment for your learning journey.

What is Educative.io?

Educative.io is an interactive learning platform designed specifically for software developers and tech professionals.

Unlike video-based platforms such as s Udemy, or Coursera, Educative uses a text-based, hands-on coding approach where learners write and run code directly in the browser.

Key Features of Educative.io:

Interactive Coding Environment — No need for setup; code directly within the platform.
Comprehensive Course Library — Covers topics like coding interviews, system design, cloud computing, DevOps, and AI.
Self-Paced Learning — Move at your own speed and revisit concepts anytime.
Structured Learning Paths — Provides guided roadmaps for mastering different skills.
Regularly Updated Courses — Keeps content fresh and aligned with industry trends.

What is Educative Unlimited?

It’s a subscription plan similar to Coursera Plus or Udemy Personal Plan which give access to text-based interactive courses on Educative.io platform, an online website famous for its System Design and Coding Courses.

The Educative Unlimited Subscription gives learners full access to all courses on the platform. Instead of purchasing individual courses, subscribers can explore hundreds of courses under a single plan.

Pricing for Educative Unlimited

As of 2026, Educative offers two main pricing options:

Annual Plan — Costs $16.66/month (billed annually at $199.99).
Monthly Plan — Costs $59/month, making the annual plan the better deal.
Two Year Plan — The most popular premium plan cost $14/ month and billed every 2 years $314 while original price is $698.

Educative often offers discounts, so checking for promotional offers can help you get a better deal. For example, right now they are offering a huge 50% discount now.

Here is the link to get your discount — Educative Unlimited Subscription

Who Should Consider Educative Unlimited?

Educative Unlimited is best suited for:

Aspiring and experienced developers preparing for coding interviews (FAANG and other top tech companies).
Software engineers looking to level up in system design and scalability concepts.
Professionals transitioning into DevOps, Cloud Computing, or AI/ML.
Developers who prefer reading and interactive coding over watching videos.

If you fall into any of these categories, Educative.io can be a strong investment.

5 Best Courses on Educative.io (Included in Unlimited Subscription)

Here are some of the top-rated courses that make Educative Unlimited worth considering:

1. Grokking the Coding Interview

Why it’s worth it: Covers patterns for solving coding problems, making it easier to tackle LeetCode-style questions.
Ideal for: Software engineers preparing for FAANG coding interviews.

Grokking the Coding Interview Patterns — AI-Powered Course

Master 24 essential coding patterns to solve thousands of LeetCode-style questions. Efficiently prepare for coding…

www.educative.io

2. Grokking Modern System Design for Software Engineers & Managers

Why it’s worth it: Provides a structured framework for designing scalable systems like Twitter, Instagram, and Uber.
Ideal for: Developers preparing for system design interviews.

Grokking the Modern System Design Interview

The ultimate guide to System Design Interviews — developed by FAANG engineers. Master distributed system fundamentals &…

www.educative.io

3. Grokking the Machine Learning Interview

Why it’s worth it: Covers ML system design, a crucial topic for AI/ML engineers.
Ideal for: Machine learning engineers applying to top AI firms.

Grokking Coding Interview Patterns in Python

Level up your coding skills. No more passive learning. Interactive in-browser environments keep you engaged and test…

www.educative.io

4. Data Structures for Coding Interviews in Python

Why it’s worth it: Covers all key data structures in an interactive format, ideal for beginners.
Ideal for: Students and new developers looking to master DSA and senior developers preparing for coding interviews.

Data Structures for Coding Interviews in Python — AI-Powered Course

Explore proven strategies developed by FAANG engineers to ace coding interviews with a structured approach to data…

www.educative.io

5. Master AWS Certified Solutions Architect Associate SAA-C03 Exam

Why it’s worth it: Prepares learners for AWS Solutions Architect and DevOps certifications.
Ideal for: Cloud engineers and DevOps professionals.

AWS Solutions Architect Associate

Become an AWS pro with this course developed by AWS Solution Certified Architects. Get hands-on with secure, resilient…

www.educative.io

These courses alone justify the cost of Educative Unlimited, especially if you’re preparing for tech interviews or upskilling in cloud computing.

Educative Unlimited: Excel with AI-Powered Learning

Ready to level up your career? Lock in unlimited access to Educative’s entire library of 1200+ hands-on Courses…

www.educative.io

Pros and Cons of Educative Unlimited Subscription

Before you buy anything online its important to analyze its pros and cons and Educative subscription is no different but its ok if you make mistake on buying a product which is for learning but still knowing about pros and cons help you take right decision.

Pros: What Makes Educative.io Worth It?

Here are the main reasons for joining Educative.io for online learning in 2026:

1. Access to High-Quality Courses

Popular courses like “Grokking the Coding Interview” are used by thousands of FAANG interview candidates.
System design and cloud computing courses offer real-world case studies.

2. Hands-On Coding Without Setup

Unlike Udemy or Coursera, where you have to set up coding environments, Educative provides an interactive editor.
This feature saves time and makes learning smoother.

3. Great for Interview Preparation

Many Google, Meta, and Amazon engineers use Educative for interview prep.
The structured learning paths help streamline preparation.

4. Cost-Effective Compared to Buying Individual Courses

Single courses like Grokking the Coding Interview cost $79-$99.
With Educative Unlimited ($199/year), you get access to hundreds of courses, making it a better deal.

5. Frequent Updates and New Courses

Courses are updated regularly, ensuring content remains up-to-date with industry standards.

Cons: Where Educative.io Falls Short

Nothing is perfect and Educative.io is no exception, there are few things which you need to know before you pay for Educative.io subscription:

1. No Video-Based Learning

Some learners prefer video-based platforms like Udemy or Coursera.
If you enjoy watching instructors explain concepts, Educative might not be the best fit.

2. Expensive Monthly Plan

The monthly plan ($59/month) is not cost-effective compared to the annual plan ($199/year).
If you don’t plan to use the platform long-term, it may not be worth the high cost.

3. Limited Customer Support

Some users report slow response times when handling billing issues.
Make sure to cancel trials early if you don’t plan to continue.

Coursera | Degrees, Certificates, & Free Online Courses

Learn new job skills in online courses from industry leaders like Google, IBM, & Meta. Advance your career with top…

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Community Feedback: What Are Other Developers Saying?

While I have positive experience learning on Educative.io and their System Design courses and Cloud labs have helped me a lot, I have also analyzed feedback from Reddit, Twitter, and tech forums to understand how developers feel about Educative Unlimited subscription.

Positive Reviews:

Reddit user (r/cscareerquestions):
“Grokking the System Design Interview is the best resource for system design prep. Worth every penny!”

Twitter review:
“Educative’s coding interview courses helped me land a job at a FAANG company. The interactive coding experience is a game-changer!”

Negative Reviews:

Reddit user (r/programming):
“The billing system is confusing. I got charged for an extra month even after canceling.”

Product Hunt user:
“Great for text-based learning, but I prefer video-based courses for complex topics like ML.”

Overall, most negative feedback revolves around billing issues and lack of video content, while positive feedback highlights the quality of interview prep courses.

Is Educative Unlimited Worth It in 2026?

Now that we have good knowledge of what to expect on getting a Educative Unlimited subscription, let’s analyze them one last time to find out whether Educative Unlimited subscription is worth it or not?

Educative.io is definitely worth It If:
✔️ You’re preparing for coding or system design interviews.
✔️ You prefer interactive coding exercises over watching videos.
✔️ You plan to learn multiple skills (DSA, system design, cloud, DevOps, ML).
✔️ You want a cost-effective way to access premium courses.

❌ Not Worth It If:
❌ You prefer video-based learning like Udemy or Coursera.
❌ You need only one or two courses (buying them separately might be cheaper).
❌ You don’t like text-heavy learning.

If you fall into the first category, Educative Unlimited is one of the best investments you can make for career growth in 2026. If you’re unsure, try the free trial before committing.

The best thing about Educative Unlimited is that they are offering 50% discount now which means you can join it for just hal price.

Educative Unlimited: Excel with AI-Powered Learning

Ready to level up your career? Lock in unlimited access to Educative’s entire library of 1200+ hands-on Courses…

www.educative.io

Where to Subscribe to Educative Unlimited

If you find these online courses and Educative platforms useful then you can also consider getting an Educative Subscription which gives you access to their 100+ courses for just $14.99 USD per month.

Sometimes you need this flexibility of joining a course you want instead of purchasing it. It’s also a better deal if you are going to attend more than a couple of courses on Educative in a year.

Here is the link to get 👉 Educative.io Subscription — Educative Unlimited

That’s all about review of Educative.io platform for developers and programmers preparing for coding interviews. If you ask me Educative Unlimited is definitely worth it not just for preparing coding interview but also to learn modern technology like AWS, Microservices, System Design, and Software architecture.

Other Educative Resources You may like to explore

Thank you for reading this article so far. All the best for your learning journey in 2026, if you have any doubts or questions, feel free to ask in the comments.

Final Tip: If you’re preparing for tech interviews, start with Grokking the Coding Interview and Grokking System Design Interviews — these two courses alone justify the subscription cost.