Contents
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- AI and LLM fundamentals
- Python for AI engineers
- Embeddings
- Vector databases and search
- RAG, beginner to advanced
- Agents and agent patterns
- LangChain
- LangGraph, in depth
- Modern agent frameworks
- Deterministic and agentic workflows
- Workflow orchestration
- MCP
- AI memory
- AI security
- Guardrails
- Evaluation
- Observability
- Cost and performance
- AI gateways
- Multimodal AI
- Local AI
- Fine-tuning
- Cloud AI
- MERN and AI
- MongoDB and AI
- AI system design
- Insurance reference project
- Practical project roadmap
- Interview questions with answers
- Senior decision framework
- Final interview cheat sheet
Adapted from 13_AI.MD · “Contents”. Code examples are study fragments. Difficulty and core labels are editorial estimates; version-specific behavior should be checked against your project.