Skip to content
Nitmonk
Free · self-paced · 51 hours

The Complete AI Agent Engineering Course

Everything from LLM foundations to production agents, Python, AWS and interview prep — taught in order, with the study notes for each lesson.

Start the course Create a free account

Every video is free · a free account unlocks the study notes

51h
of content
61
lessons
18
study notes
4
tracks

What you'll learn

Everything an AI agent engineer needs, in one course

  • How LLMs work

    Tokens, embeddings, vectors and self-attention, the foundation every agent sits on.

  • Prompt engineering

    The prompting patterns, examples and format control agents rely on.

  • RAG, end to end

    Embeddings, vector search, Pinecone, vector databases and 20+ chunking techniques.

  • Agent architecture

    Tool calling, ReAct, memory, traces and evals, and how the loop fits together.

  • Enterprise agent patterns

    10+ agent patterns and the 60 bottlenecks real enterprise systems hit.

  • MCP and context engineering

    Model Context Protocol from zero to production, plus 23+ context and memory techniques.

  • Evals and observability

    How LLM evals work with Ragas, Langfuse and DeepEval, and how to cut token cost.

  • Hands-on builds

    LangChain + LangGraph agents from scratch, multi-agent memory, VLMs and real projects.

  • Python for AI engineers

    Closures, decorators, async, typing, Pydantic and the DSA interviews expect.

  • Interview preparation

    100+ questions real MNC interviews ask about AI agents, and how to answer them.

From learners

Learners are landing AI engineering roles

Real messages and comments from people learning with these videos.

2–3 offers → Senior AI EngineerWhatsApp message: Hey bro, just wanted to genuinely thank you for all the AI content you've shared on YouTube. There are so many AI playlists out there, but what I really liked about yours is that you teach everything in a practical, real-world way, rather than just theory. It feels like you're actually sharing things based on how you've worked on them in real projects, and that made a huge difference for me. I completed your playlist, and it helped me crack multiple interviews, get 2–3 offers, and reach the final stage of 4–5 companies. Finally, I've decided to join [company hidden] as a Senior AI Engineer. Your content genuinely played a big role in this journey. Really appreciate all the effort you put into teaching. Once again, thanks a lot
Learner, now a Senior AI EngineerMessage on WhatsApp · name hidden for privacy
Cleared the Infosys interviewWhatsApp message: Hello Abhishek, I am one of the subscribers of your YouTube channel since u had around 1.5k subscribers. I am a regular on your channel and try to cover all the gen ai, agentic ai related videos and study materials. I recently completed Infosys recruitment process and will receive the offer in coming week. Thanks a lot for the effort that you are putting. Your videos on interview questions helped me a lot. Almost all topics that were asked in my interview were already covered by you. Thank you once again.
Subscriber since the channel had 1.5K subscribersMessage on WhatsApp · name hidden for privacy

Your learning path

Four tracks, one job-ready AI engineer

Start with the core course, sharpen your Python, prepare for interviews, then watch the ideas applied in real builds.

  1. Track 01Core CourseFrom LLM foundations to production agents — watch in order, top to bottom.23 lessons · 24h 31mView lessons
  2. Track 02Python for AI EngineersThe Python foundation and DSA every AI engineer needs — closures, decorators, async, typing and Pydantic.8 lessons · 3h 12mView lessons
  3. Track 03Interview Preparation100+ questions real MNC interviews ask — and how to answer them.7 lessons · 7h 46mView lessons
  4. Track 04Builds & ExperimentsReal projects, tool tests and vibe-coded startups — the roadmap applied end to end.23 lessons · 15h 38mView lessons

Curriculum

Course content

4 tracks · 61 lessons · 51h 7m total length

From LLM foundations to production agents — watch in order, top to bottom.

More study material

Comprehensive notes that span the whole course.

Complete AI Agent Study Material

FAQ

Frequently asked questions

Is this AI Agent Engineering course really free?

Yes. All 61 video lessons are free to watch on YouTube. A free Nitmonk account unlocks the study notes. There is no paid tier for this course.

How long does it take to complete the course?

The course has about 51 hours of video across 61 lessons in 4 tracks. Most learners finish the core course first and work through the Python, interview and builds tracks alongside it.

What do I need to know before starting?

Basic programming experience helps. If your Python is rusty, start the Python for AI Engineers track alongside the core course. No machine learning background is required.

In what order should I watch the lessons?

Watch the Core Course top to bottom: it starts with how LLMs work and builds up to production agents. The Python track can run in parallel, then use Interview Preparation and Builds & Experiments to apply what you learned.

What topics does the course cover?

LLM fundamentals, tokens and embeddings, prompt engineering, RAG and vector databases, chunking, agent architecture and tool calling, enterprise agent patterns, MCP, context engineering, agent memory, evals, LangChain and LangGraph, VLMs, Python for AI and AI engineer interview prep.

What are the study notes?

Interactive study notes that go with the lessons: 18 notes covering topics like LLM foundations, RAG chunking, agent design patterns, MCP, context engineering and evals. Create a free account to open them.

Ready to go from zero to job-ready?

Create a free account to unlock every study note, track your progress and ask doubts.

Sign up free Subscribe on YouTube