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
This is the only course which finally teaches how to fine-tune your own LLM.
Nicely explain different transformers and models with example notebooks.
the course has been designed in a well structured way from bert model to advanced lora qlora techniques and easy to understand the concept
This Udemy course delivered a structured learning path with clear, up-to-date resources and practical code examples.
The instructor explains in a very organised way which gives us an idea what are the fundamentals that are required.
This was a great course. I picked up a lot of new things, and the instruction was excellent. I'm really glad I enrolled.
As someone who struggled with Blender for months, this course finally made things click for me. The teaching style is simple, clear, and very engaging.
Really good course
This course is well structured, every session is easy to digest and very well explained. Kudos to the lecturer and team.
Great content, comprehensive code documentation, flow and topic selection. Laxmi provides a good learning experience.
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.
The course is very excellent especially to start learning llms.
This was a comprehensive and enjoyable course with some great projects at the end that helped reinforce the main concepts.
This is the one of the best course in this platform to automate the blender with Claude!!!!!
I have learned a lot in this course, thank you
ótimo curso para iniciar em contruções de agentes!
Reviews from 200,000+ students on Udemy and YouTube
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.
We ran ternary Bonsai 2 27B and its 4-bit parent Qwen 3.8 27B on the same engine on a 36GB MacBook Pro. Quality matched, Bonsai used 7 GB less memory, decoded faster, and held a 148K-token prompt that Qwen could not.
Every word in a transformer asks a question, advertises what it knows, and holds an answer. Those are query, key and value, and this is how they work.
A picture by picture walk through the sparse attention inside DeepSeek V4.1 Flash: the lightning indexer, the 512 entry pick, and how CSA2 shares one pick across many layers.
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.
IBM Granite 4.2 Dropped Mamba: 34.4 GB KV Cache on a 32 GB GPU
Do You Know How GLM 5 3 and GLM 5 3 Flash Works? DSA, KDA and KV Cache Explained
LangChain Tutorial for Beginners: Build a RAG System with Langchain and RAGWire
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.
