Module - LLM- Day1 - Course Structure | Master Agentic AI

🔥 LLM Module - Day 1 | Course Structure & Roadmap | GenAI Elite Welcome to Day 1 of the LLM Module in the GenAI Elite program — the only production-focused GenAI mentorship built for senior engineers (8-15 years experience) who want to make a real career shift into AI/ML roles. In this session, we break down the complete course structure, what you'll learn, how the modules connect, and what makes this program different from every other GenAI course out there — no fluff, no beginner-level recycled content, just production-grade depth. 🧠 Full Module Roadmap: ✅ Python Foundations for AI/ML ✅ Deep Learning (MLPs, CNNs, RNNs, Transformers) ✅ LLM Internals & Transformer Architecture ✅ Prompt Engineering & Multi-Pass Prompting ✅ Vector Databases & Embedding Strategies ✅ RAG Pipelines (Chunking, Retrieval, Evaluation with RAGAS) ✅ Graph RAG with Neo4j & LlamaIndex ✅ Agentic Systems with LangGraph (Human-in-the-Loop, Subgraphs, Orchestrator-Worker) ✅ MCP (Model Context Protocol) & Tool Integration ✅ Memory Management & Context Engineering for Multi-Agent Systems ✅ Production Deployment with FastAPI & Async Python ✅ Capstone Projects on Real Enterprise Domains 🚀 JOIN THE UPCOMING BATCH OF GenAI Elite: 👉 https://connect.genaielite.com/meeting This is a cohort-based, personal mentorship program — not a recorded dump. Limited seats per batch. If you're a senior engineer tired of surface-level AI content and want to actually build production-grade GenAI systems, this is your move.