Preparation
Interview preparation sessions covering AI/ML topics
1Session 1: LLM Fundamentals — How Large Language Models Actually Work2Session 2: Prompt Engineering & Context Engineering3Session 3: RAG Fundamentals — The One Topic That Lands You the Job4Session 4: Advanced RAG Patterns5Session 5: LangChain, LangGraph & Agent Frameworks6Session 6: Multi-Agent Systems & Orchestration7Session 7: Agent Memory, State & Planning8Session 8: Tool Integration, Function Calling & MCP9Session 9: Guardrails, Safety & Responsible AI10Session 10: Evaluations — Online & Offline11Session 11: LLMOps, Observability & Cost Management12Session 12: Prompt Management & Dataset Management13Session 13: Vector Databases & Embeddings Deep Dive14Session 14: Performance Optimization — Latency, Cost & Caching15Session 15: Production Deployment & Infrastructure for AI16Session 16: System Design & Behavioral Prep17Session 17: Fine-Tuning — PEFT, LoRA & Training Pipelines18Session 18: AI-Assisted Development — Cursor, Claude Code & Modern AI Workflows19Session 19: Technical Leadership for Lead AI Engineer Roles