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
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.
IBM dropped the Mamba hybrid in Granite 4.2, so we measured what that costs: KV cache per token, real usable context, decode speed with and without MTP, and accuracy on a harder eval set.
We put Ornith 1.5 9B and 35B-A3B on one RTX 5090 and measured nine things, including why the 35B is the only large model here that delivers its full 262k context.
We diffed all 866 GGUF tensors of an uncensored Qwen 3.8 27B against the original and found 131 matrices edited along one shared direction, with no measurable cost to quality.
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.
Qwen 3.8 vs Qwen 3.6 vs Qwen 3.5: What Actually Changed
Qwen 3.8 27B vs Muse Glimmer vs Gemma 4 - DFlash Made Glimmer 3x Faster
Qwen 3.8 27B Speed Settings Explained: MTP, KV Cache and Flash Attention
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.
What Students Say About Us
“The instructor explained clearly and its examples were easy to implement. I recommend it for introducing yourself into the latest advancements in transformers.”
“This is a nice hands-on video. The contents enhance the knowledge of fine tuning the model. I have also found that the 'theory' parts are very worth to learn.”
“The lecture is well-organized and delivered clearly, and easy to learn.”
