Multi-Modal RAG & AI Agents Course (Hands-On, 10+2 Weeks)
Master multimodal RAG & AI agents in 10+2 weeks. Build end-to-end systems with vector search, pgvector, LangGraph, evaluation, and cloud deployment. Project-based, mentor-led, career-focused.
Must Watch - Overview of LMS and Support using Discord
Introduction - Setup Development Environment on Windows
Getting Started with Google Colab
Getting Started with GCP
Setup VS Code and Git Bash on Windows
Setup GitHub Copilot and Python - VS Code
Setup gcloud CLI on Windows
Setup Cursor on Windows
Getting Started with Meta LlaMa on GCP
Getting Started with Vertex AI using Colab
Conclusion to Setup Development Environment
Introduction - Setup Development Environment on Mac
Getting Started with Google Colab
Getting Started with GCP
Setup VS Code and GitHub Copilot on Mac
Install Google Cloud CLI on Mac
Setup Cursor on Mac
Getting Started with Meta LlaMa on GCP
Getting Started with Vertex AI using Colab
Conclusion to Setup Development Environment
Live Session - Kickoff & Thin Slice Multimodal RAG
Getting Started with the Session - Presentation
Overview of Car Specs (PDFs) - Data Sets used for Demos - Presentation
Car Specs (PDFs) - Data Sets with Instructions
Introduction to Multi Modal RAG - Presentation
Text only RAG using Langchain and Chroma - Lab
Evaluating Understanding of the Concepts
Data Set for the assignment (LinkedIn Profiles)
Assignment — Resume Search with Chroma + Embeddings
Live Session
YouTube Pre-recorded Session
Introduction to LangChain and its eco system - Presentation
Getting Started with Chromadb and LangChain
Chunking and Storing using LangChain
Quiz - Chromadb and LangChain Concepts
Assignment 1: on Metadata Filtering using Direct and LangChain.ipynb
Live Session
YouTube Pre-recorded Session
Similarity Search and Generate using LangChain
Getting Started with Streamlit
Assignment 2: Retrieve, Augment and Generate.ipynb