Full stack generative and Agentic AI with python (Udemy.com)
Hands-on guide to modern AI: Tokenization, Agents, RAG, Vector DBs, and deploying scalable AI apps. Complete AI course
Created by: Hitesh Choudhary
Last updated December 2025
What you will learn
- Write Python programs from scratch, using Git for version control and Docker for deployment.
- Use Pydantic to handle structured data and validation in Python applications.
- Understand how Large Language Models (LLMs) work: tokenization, embeddings, attention, and transformers.
- Call and integrate APIs from OpenAI and Gemini with Python.
- Design effective prompts: zero-shot, one-shot, few-shot, chain-of-thought, persona-based, and structured prompting.
- Run and deploy models locally using Ollama, Hugging Face, and Docker.
- Implement Retrieval-Augmented Generation (RAG) pipelines with LangChain and vector databases.
- Use LangGraph to design stateful AI systems with nodes, edges, and checkpointing.
- Understand Model Context Protocol (MCP) and build MCP servers with Python.
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.4 out of 5higher than 28% of them
- Reviews10,110#20 of 462 by number of reviews
- Length32.6 hourslonger than 90% of them
- Last updatedDecember 2025more recently than 54% of them
Course Description
Welcome to the Complete AI & LLM Engineering Bootcamp – your one-stop course to learn Python, Git, Docker, Pydantic, LLMs, Agents, RAG, LangChain, LangGraph, and Multi-Modal AI from the ground up.
This is not just another theory course. By the end, you will be able to code, deploy, and scale real-world AI applications that use the same techniques powering ChatGPT, Gemini, and Claude.
What You’ll Learn
Foundations
Python programming from scratch — syntax, data types, OOP, and advanced features.
Git & GitHub essentials — branching, merging, collaboration, and professional workflows.
Docker — containerization, images, volumes, and deploying applications like a pro.
Pydantic — type-safe, structured data handling for modern Python apps.
AI Fundamentals
What are LLMs and how GPT works under the hood.
Tokenization, embeddings, attention, and transformers explained simply.
Understanding multi-head attention, positional encodings, and the "Attention is All You Need" paper.
Prompt Engineering
Master prompting strategies: zero-shot, one-shot, few-shot, chain-of-thought, persona-based prompts.
Using Alpaca, ChatML, and LLaMA-2 formats.
Designing prompts for structured outputs with Pydantic.
Running & Using LLMs
Setting up OpenAI & Gemini APIs with Python.
Running models locally with Ollama + Docker.
Using Hugging Face models and INSTRUCT-tuned models.
Connecting LLMs to FastAPI endpoints.
Agents & RAG Systems
Build your first AI Agent from scratch.
CLI-based coding agents with Claude.
The complete RAG pipeline — indexing, retrieval, and answering.
LangChain: document loaders, splitters, retrievers, and vector stores.
Advanced RAG with Redis/Valkey Queues for async processing.
Scaling RAG with workers and FastAPI.
LangGraph & Memory
Introduction to LangGraph — state, nodes, edges, and graph-based AI.
Adding checkpointing with MongoDB.
Memory systems: short-term, long-term, episodic, semantic memory.
Implementing memory layers with Mem0 and Vector DB.
Graph memory with Neo4j and Cypher queries.
Conversational & Multi-Modal AI
Build voice-based conversational agents.
Integrate speech-to-text (STT) and text-to-speech (TTS).
Code your own AI voice assistant for coding (Cursor IDE clone).
Multi-modal LLMs: process images and text together.
Model Context Protocol (MCP)
What is MCP and why it matters for AI apps.
MCP transports: STDIO and SSE.
Coding an MCP server with Python.
Real-World Projects You’ll Build
Tokenizer from scratch.
Local Ollama + FastAPI AI app.
Python CLI-based coding assistant.
Document RAG pipeline with LangChain & Vector DB.
Queue-based scalable RAG system with Redis & FastAPI.
AI conversational voice agent (STT + GPT + TTS).
Graph memory agent with Neo4j.
MCP-powered AI server.
Who Is This Course For?
Beginners who want a complete start-to-finish course on Python + AI.
Developers who want to build real-world AI apps using LLMs, RAG, and LangChain.
Data Engineers/Backend Developers looking to integrate AI into existing stacks.
Students & Professionals aiming to upskill in modern AI engineering.
Why Take This Course?
This course combines theory, coding, and deployment in one place. You’ll start from the basics of Python and Git, and by the end, you’ll be coding cutting-edge AI applications with LangChain, LangGraph, Ollama, Hugging Face, and more.
Unlike other courses, this one doesn’t stop at “calling APIs.” You will go deeper into system design, queues, scaling, memory, and graph-powered AI agents — everything you need to stand out as an AI Engineer.
By the end of this course, you won’t just understand AI—you’ll be able to build it.
Instructor Details
- 4.4 Rating
10,110 Reviews
Hitesh Choudhary
My name is Hitesh Choudhary, a retired corporate professional who has seamlessly transitioned into a full-time YouTuber. With a rich history as the founder of LCO (acquired) and a former CTO at iNeuron and Senior Director at PW, I bring a wealth of experience in building software and companies. My journey in the tech world has endowed me with unique insights and expertise, which I am passionate about sharing.
On YouTube, I manage two thriving channels—one boasting 1 million subscribers and the other with 300,000—demonstrating my ability to connect with and educate a vast audience. My travels to 39 countries have enriched my understanding and provided a global perspective that I incorporate into my content.
My hallmark is making the toughest topics easy to understand, a skill that has earned me a dedicated following. I am committed to educating and inspiring a diverse audience worldwide, making complex subjects accessible and engaging. Join me on Udemy, where I bring my extensive knowledge, practical experience, and unique teaching style to help you master new skills and advance your career.
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Reviews
By Parth Santosh Hadkar on 8/27/2026
Great course for beginners! It covers multiple areas of programming and gives you a good overall understanding of the key concepts. For experienced developers, it’s a good way to refresh and expand your knowledge. However, if you’re looking for deep, in-depth coverage of each topic, this may not be the course for you. Overall, a great choice for beginners and techies who want to build a solid understanding of the fundamentals without going too deep.
By Milind pasi on 8/27/2026
Coming from a background of 15+ years in MERN stack development, I really appreciated how this course made Python and AI concepts approachable. The pacing is beginner-friendly, and the sections on agentic programming were especially useful for getting a practical starting point. Highly recommend for experienced developers looking to expand into AI.
By Ajay Kumar Shah on 8/25/2026
More than half the course was spent on Python, Git/GitHub, and Docker that was unnecessary for me — I'd expected the focus to be on AI throughout. That said, the AI sections were fantastic. I came away with a much better understanding of LLMs, agents, vector databases, embeddings, and how agents store and retrieve memory. My main gap: I was hoping for a full end-to-end project to tie it all together, and that wasn't included.
By Yele Navin Kumendra on 8/8/2026
"This is an absolutely fantastic course for anyone looking to get into AI! Piyush Garg has a unique ability to break down complex Artificial Intelligence concepts into simple, easily digestible lessons. The pacing is perfect, taking you from the absolute basics to advanced, real-world implementations. What I loved most is the hands-on approach—we didn't just learn theory; we actually built practical projects that I can now showcase in my portfolio. Highly recommended for developers looking to upskill and integrate AI into their tech stack!"
By James Walker on 7/7/2026
I really enjoyed the review of Python and how it led into the foundation of AI. The first few sections gave me a good introduction and helped me understand what I can expect as I continue learning more about AI. I’m excited to dive deeper and learn more about AI, especially its possibilities and how it can be used in different areas. Overall, I think this is a great starting point for learning the ins and outs of AI, and I’m looking forward to seeing what I can learn and apply as the course continues.
By Biplob Deb Nath on 7/7/2026
he course has been well-structured and easy to follow. The explanations are clear, and the hands-on examples have helped me understand Python fundamentals and GPT concepts more effectively. I especially appreciate the practical approach, which makes it easier to connect theory with real-world applications. I'm looking forward to the remaining modules
By Nethravathi Nagappa on 6/11/2026
I'm a .Net developer wanted to learn Python. It was up to date and very effective learning course. I'm pretty much confident to work on Python projects now.
By Ajay Yadav on 6/8/2026
Very good explanation and examples of Python. This course is too good to understand the Agent AI. Very easy and good explanation of AI concepts. Both instructors explained very well.
By Shivang pandey on 6/1/2026
Thank you for creating such practical and industry-focused content. As an experienced iOS developer, I found many ideas that I can apply in real-world projects. I have a small request: Please create more detailed lectures on MCP (Model Context Protocol), including advanced real-world implementations and integrations. When I purchased the course, a Certificate of Completion was mentioned. I have completed 100% of the course, but currently I am unable to find the certificate section on Udemy. Could you please help me regarding this?
By Sagar Sethia on 5/28/2026
Thanks both tutor for this amazing course , you teach difficult topics in a very nice and easy way. One of the best course for python basic , learn python with having different types of tea. Thanks Hitesh Also very nicely articulate course on Gen AI , Langraph , Lang Chain . Thanks Piyush for this. If you could elaborate more on MCP that would be great and one more request to both if we get your black board that would be super useful :) Thank you both
Quality Score
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Overall Score : 88 / 100












