Aarav Mehta

Curriculum coverage by module

First-attempt mastery signal

Strong areas

• • Day 5 — Prompt Engineering Patterns
• • Day 9 — Embeddings & Semantic Similarity
• • Day 13 — RAG Architecture Fundamentals
• • Day 14 — Query Rewriting & Expansion
• • Day 16 — Grounding, Citations & Hallucination Control
• • Day 17 — Tool Calling Fundamentals

Needs deeper validation

• • Day 3 — APIs, Async & Streaming Basics (4 attempts)
• • Day 7 — Model Selection & Cost Tradeoffs (4 attempts)
• • Day 12 — Metadata Filtering & Hybrid Search (4 attempts)
• • Day 18 — Agent Loops & Planning (3 attempts)
• • Day 2 — Python for AI Systems (2 attempts)
• • Day 4 — How LLMs Work: Tokens & Context (2 attempts)

Unvalidated (skipped)

• • Day 1 — AI Engineering Landscape
• • Day 6 — Structured Outputs & JSON Schema
• • Day 8 — Text Chunking Strategies
• • Day 10 — Retrieval & Matching Engine
• • Day 11 — Vector Databases in Production
• • Day 15 — Reranking & Context Compression
• • Day 20 — Retrieval Agents
• • Day 23 — Model Context Protocol

Skipped missions are explored, not assumed weak.