Welcome to my GenAI learning journey! This repo is a personal notebook where I track everything I learn and build throughout the GenAI Cohort course by Hitesh Choudhary & Piyush Garg — a hands-on deep dive into building real-world GenAI applications.
This course is practical and project-focused, designed to help developers like me understand and use Generative AI tech stacks (LLMs, vector stores, agents, etc.) to build scalable AI applications. We're skipping the math and focusing on real-world problem-solving.
- Fundamentals of LLMs & Generative AI
- AI Agents and Agentic Workflows
- Chat over Large Documents using vector stores (Qdrant, PGVector, Pinecone)
- Retrieval-Augmented Generation (RAG)
- Memory-aware Agents with Graph DBs (Neo4j)
- Multi-modal LLM Applications
- Secure and Controlled AI Workflows (Llama-3, Guardrails, MCP)
- Fine-tuning and Evaluation Techniques
- Languages: Python, JavaScript
- Frameworks: LangChain, LangGraph, LangSmit
- Tracing/Monitoring: Langfuse (Docker)
- Vector Stores: PGVector, Qdrant, Pinecone
- Graph DB: Neo4j
- Deployment: MCP Server, AWS
- LLMs: OpenAI, Claude, DeepSeek, Gemini, Llama-3, Gemma
- Learning Tracking Tools: Notion, Hashnode
| Date | Topic/Concept | Notes / Blog / Repo |
|---|---|---|
| 2025-04-07 | Decoding AI Jargons With Chai | • Blog |
| 2025-04-10 | Decoding AI Jargons With Chai | • Blog |
I’ll keep updating this table regularly 🚀
I’m documenting this journey through blogs. Here are a few I’ve written so far:
Follow more on My Blog
Hi, I’m [Sandeep]! I’m a developer passionate about AI, product-building, and learning in public. This repo is my playground and portfolio as I explore Generative AI and build meaningful stuff.
Let’s connect:
Feel free to open issues or PRs. Always happy to chat, collaborate, or brainstorm ideas 💬