Code-first AI for production
Learn to build and deploy machine learning, RAG, and AI agent systems through practical, step-by-step projects.
200K+
Learners
IIT KGPIIT Kharagpur
Alumnus
4.8★
Instructor rating
Stay in the loop
Short videos, new tutorials and course updates on Instagram and WhatsApp.
Guided Roadmaps
Follow a sequenced roadmap instead of piecing together disconnected tutorials.
A structured, progressive roadmap for developers seeking to master AI agents, covering Python foundations, LangChain, LangGraph, and private multi-agent RAG.
A comprehensive curriculum taking you from zero programming knowledge to professional data manipulation, mathematical visualization, and core ML model building.
Latest from the library
Start with recent code-first guides, or filter the library by the skill you are building.
One big prompt vs a prompt chain on Amazon's segment margins with Qwen 3.8: the model reads and writes, Python does the math, and a checker prompt catches the errors.
We tested Jev 1.13 as a router for 200 Banking77 card messages with 10 intents, reached 0.985 accuracy with option descriptions, and used its confidence to pick an auto-answer cut-off that still covers 90% of messages.
Hosted Jev 1.13 scored 0.970 and Laya on a local RTX 5090 scored 0.875 on the same 10-intent question over 200 bank card messages, while Laya answered one request in 20.5 ms against 654 ms for Jev.
Meet your instructor
I'm Laxmi Kant Tiwari, IIT Kharagpur alumnus, founder with a successful startup exit, and an engineer with 10+ years across industry and academia. Everything here is taught the way real production systems are built.
Read my storyFree Video Tutorials
Full video walkthroughs, free: new tutorials every week.
Byte Pair Encoding Explained | BPE Tokenizer Step by Step
Tokenization in LLM Explained: 4 Ways to Split Text for LLMs
How Does ChatGPT Remember? Context Window Explained | AI System Design Interview
In-Depth Courses
Go deeper with complete projects, private repositories, and certificates.
Master Langchain v1, Local LLM Projects, Ollama, DeepSeek, LLAMA 3.2, Complete Integration Guide.
Agentic RAG and Chatbot, AI Agent, DeepSeek, LLAMA 3.2 Agent, FAISS Vector Database.
Build MCP servers & clients with Python, Streamlit, ChromaDB, LangChain, LangGraph agents, and Ollama integrations.
Explore all available curriculum packages with our worldwide student ratings and pre-applied coupons.
Student Reviews
Reviews from students on Udemy, in their own words.
4.8
Instructor rating
200,000+ students learning on Udemy and YouTube.
I really like this course. It explains AI step by step in a simple and clear way. This should be the first course anyone takes to truly understand AI.
This is the only course which finally teaches how to fine-tune your own LLM.
Great content, comprehensive code documentation, flow and topic selection. Laxmi provides a good learning experience.
The course is very excellent especially to start learning llms.
This was a great course. I picked up a lot of new things, and the instruction was excellent. I'm really glad I enrolled.
Really good course
This course is well structured, every session is easy to digest and very well explained. Kudos to the lecturer and team.
the course has been designed in a well structured way from bert model to advanced lora qlora techniques and easy to understand the concept
The instructor explains in a very organised way which gives us an idea what are the fundamentals that are required.
This is the one of the best course in this platform to automate the blender with Claude!!!!!
ótimo curso para iniciar em contruções de agentes!
