Level 2: Practitioner

This level builds on foundations to implement real-world AI solutions. You'll learn advanced prompting, build RAG systems, use LangChain, and deploy to production.

🎯 2.01 – Advanced Prompt Engineering

Chain-of-Thought, Tree of Thoughts, Self-Consistency, ReAct, and prompt optimization techniques.

⏱️ 75 min read | 🎯 L2 | 🎨 Advanced

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📚 2.02 – RAG Deep Dive

Advanced retrieval techniques: chunking strategies, embedding models, hybrid search, reranking, evaluation.

⏱️ 90 min read | 🎯 L2 | 🧠 Architecture

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🦜 2.03 – LangChain & LlamaIndex

Building production-ready AI applications with LangChain chains, agents, memory, and tools.

⏱️ 120 min read | 🎯 L2 | 🔧 Framework

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⚙️ 2.04 – Production AI

Streaming, caching, rate limiting, cost optimization, monitoring, and prompt versioning.

⏱️ 90 min read | 🎯 L2 | 🚀 DevOps

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🎯 Level 2 Completion Criteria

✅ Implement advanced prompt engineering techniques (CoT, few-shot, ReAct)
✅ Build and deploy a production RAG system
✅ Use LangChain for chains, agents, and memory
✅ Optimize AI applications for cost and performance

📗 Level 2: Practitioner

🎯 2.01 – Advanced Prompt Engineering

📚 2.02 – RAG Deep Dive

🦜 2.03 – LangChain & LlamaIndex

⚙️ 2.04 – Production AI

🎯 Level 2 Completion Criteria