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.
We read the GGUF headers of Qwen 3.8 27B, Qwen 3.6 27B, and Qwen 3.5 27B and ran 397 measured generations on one RTX 5090 to find where the gains between the three releases really come from.
We asked Qwen 3.8 27B, Muse Glimmer 30B, and Gemma 4 26B the same twelve questions ten times each on one RTX 5090 to measure which local model gives the same answer twice.
We ran 45 llama.cpp configurations of Qwen 3.8 27B on one RTX 5090 to find which settings make it faster: draft depth, KV cache type, context size, and reasoning effort.
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.
LangChain Tutorial for Beginners: Messages, Roles and LangSmith Setup
Run Claude Code Free on Your Own GPU with a Local Model on Ollama
Qwen 3.8 on Ollama vs Muse Glimmer vs Gemma 4 - Local LLM Coding Test on Ollama
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.”
