12 Sections
24 Lessons
10 Weeks
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Section 1 – Foundations of LLM Engineering
2
1.1
Week 1 • Modern LLMs Topics GPT & BERT Tokenization RoPE Mixture of Experts (MoE) Flash Attention
30 Minutes
1.2
Project: Run Open-Source LLMs
10 Minutes
Week 2 • Prompt Engineering
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2
2.1
Topics: Zero-Shot Prompting Few-Shot Prompting Chain of Thought ReAct Framework Structured Outputs
45 Minutes
2.2
Project: AI Prompt Assistant
45 Minutes
Week 3 • RAG Fundamentals
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2
3.1
Topics: Embeddings Chunking Vector Databases Semantic Search
10 Minutes
3.2
Project: PDF Question Answering System
10 Minutes
Week 4 • Advanced RAG
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2
4.1
Topics: Self-RAG CRAG Adaptive RAG GraphRAG Re-ranking
10 Minutes
4.2
Project: Enterprise Knowledge Assistant
10 Minutes
Section 2 – Agentic AI Development
Week 5 • LangChain
2
5.1
Topics: Chains LCEL Retrievers Memory Agents
10 Minutes
5.2
Project: SQL & Document Chatbot
15 Minutes
Week 6 • LangGraph & Agentic AI
2
6.1
Topics: State Graphs Multi-Agent Systems Tool Calling Reflection
6.2
Project: Autonomous Research Agent
Week 7 • LLM Evaluation
2
7.1
Topics: LangSmith Ragas DeepEval TruLens Hallucination Detection
7.2
Project: Evaluate an AI Assistant
Week 8 • Ollama & Local LLMs
2
8.1
Topics: Ollama GGUF Models Quantization Local APIs
8.2
Project: Offline Local RAG Chatbot
Section 3 – Production AI Systems
Week 9 • Fine-Tuning LLMs
2
9.1
Topics: SFT LoRA QLoRA PEFT DPO
9.2
Project: Domain-Specific LLM
Week 10 • AI Agents & MCP
2
10.1
Topics: Model Context Protocol (MCP) Memory Planning Browser Tools File Tools API Tools
10.2
Project: Personal AI Agent
Week 11 • Production Systems
2
11.1
Topics: FastAPI Docker Redis Security Monitoring
11.2
Project: Enterprise LLM API Deployment
Week 12 • Capstone Project
2
12.1
End-to-End LLM Engineering & Agentic AI
12.2
Final Project Production-Ready AI Application
Advanced LLM Engineering, RAG & Agentic AI
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