Top 5 Udemy Courses for AI Engineering Interviews in 2026

My favorite Udemy courses to prepare for AI Engineer Interviews in 2026

Hello guys, AI engineering interviews have become some of the toughest technical interviews in the industry. Companies are no longer satisfied with basic machine learning; they expect depth in LLM architecture, RAG systems, embeddings, prompt engineering, vector search, model fine-tuning, and practical deployment.

The bar has risen dramatically in last 2 years, and so has the level of competition.

The good news is that you can prepare effectively if you follow structured learning paths taught by experienced instructors who’ve been working directly with LLMs, GenAI frameworks, and real-world production architectures.

Udemy has emerged as one of the most accessible platforms for AI engineers to upskill, thanks to its hands-on projects, comprehensive curriculums, and real interview preparation content.

After reviewing dozens of AI and LLM courses in the last few months, I’ve shortlisted the Top 5 Udemy Courses for AI Engineering Interviews in 2026. These courses are specifically curated to help you master the concepts, architectures, and practical skills that recruiters expect today.

Let’s dive in.

5 Best Udemy Courses to Prepare for AI Engineer Interviews in 2026

Without any further ado, here are the top 5 Udemy courses you can join to learn essential skills like RAG, LLM Engineering, AI agents etc to prepare for any AI Engineer interviews in 2026

1. AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents

If you’re preparing for AI engineering roles at companies building large-scale generative AI systems, this course should be at the top of your list. It teaches the foundational and advanced concepts required to build, deploy, optimize, and scale modern AI systems.

You’ll learn LLM engineering fundamentals, Retrieval-Augmented Generation, quantization, LoRA, QLoRA, evaluation techniques, vector stores, and agent frameworks. The projects mirror real interview scenarios, making this course ideal for leveling up quickly.

What you will learn:

LLM architecture, transformer internals, and fine-tuning
RAG pipelines end-to-end
LoRA and QLoRA for efficient training
AI Agents and tool calling
Vector databases and production considerations
Real-world scenarios commonly asked in interviews

Perfect for candidates preparing for roles like LLM Engineer, AI Engineer, Applied Scientist, and ML Platform Engineer.

Here is the link to join this course — AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents

2. Become an LLM Engineer in 8 Weeks: Build and Deploy 8 LLM Apps

This is one of the most practical, project-driven courses available for LLM engineers. Instead of long theoretical modules, this course takes you through eight real LLM application builds — each of them covering an interview-relevant concept.

This course is ideal if you prefer learning by doing, or if you need a strong GitHub portfolio before interviewing.

Highlights:

Build and deploy 8 LLM production-grade apps
Work with RAG, embeddings, vector search, LoRA, agents, and evaluation
Covers essential backend + AI integration workflows
Teaches deployment on modern AI stacks
Clear step-by-step explanations for each architecture

If you’re transitioning from software engineering to AI engineering, this is one of the most efficient ways to get interview-ready.

Here is the link to join this course — Become an LLM Engineer in 8 Weeks: Build and Deploy 8 LLM Apps

3. LLM & Gen AI Interview Questions (with Explanation)

Most candidates underestimate interview prep. Knowing how to build LLM apps is one thing. Answering architecture questions under pressure is another. That’s where this course shines.

It offers more than 300+ practice questions across LLMs, transformers, RLHF, embeddings, RAG architecture, multimodal systems, inference optimization, and more. Each question comes with an explanation, making it ideal for daily revision.

What’s included:

300+ interview questions
Practical explanation-based learning
Covers Llama, GPT models, Hugging Face ecosystem
Deep dives into LoRA, RLHF, tokenization, attention mechanisms
Excellent for last-mile preparation before interviews

This is one of the best “rapid revision” courses you can use in the final weeks before your interviews.

Here is the link to join this course — LLM & Gen AI Interview Questions (with Explanation)

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

This course is a complete bootcamp covering the entire AI engineering stack from Python to transformers to LangChain to Hugging Face. It is ideal for beginners entering AI engineering as well as software engineers transitioning into GenAI roles.

What you’ll learn:

Python for AI engineering
NLP foundations and tokenization
Transformer models and fine-tuning
LLM architecture and optimization
LangChain workflows and agents
APIs, deployment, and integration
Hugging Face ecosystem

Whether you’re preparing for system design rounds or hands-on coding assessments, this course gives you a solid foundation.

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

5. Complete Generative AI Course with LangChain and Hugging Face

This course combines both hands-on development and interview preparation, making it one of the most efficient courses for 2026.

You’ll learn:

LangChain internals and advanced pipelines
Hugging Face Transformers in depth
Model loading, inference optimization, quantization
Memory, tools, and advanced agent design
Practical RAG architecture with multiple vector DBs

This blend of theory, architecture design, and hands-on coding makes it perfect for intermediate-to-senior developers preparing for AI engineering interviews.

Here is the link to join this course — Complete Generative AI Course with LangChain and Hugging Face

Final Thoughts

That’s all about the best Udemy courses to prepare for AI Engineer interviews in 2026. AI engineering interviews demand more than traditional ML knowledge. You need strong fundamentals in transformers, RAG, embeddings, vector search, fine-tuning, model optimization, and prompt engineering.

These five Udemy courses offer everything you need to build real apps, strengthen your fundamentals, and prepare for actual interview questions.

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 MLOps, AIOps, and LLMOps 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.

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