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Ananya Iyer

CND-1008 · Machine Learning Engineer · 8.7 yrs · M.S. Artificial Intelligence

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Completion

55%

First-try rate

59%

Avg attempts

1.65

Consistency

55%

Curriculum coverage by module

First-attempt mastery signal

Attempts by topic (higher = needs validation)

Strong areas

  • • Day 5 — Prompt Engineering Patterns
  • • Day 8 — Text Chunking Strategies
  • • Day 12 — Metadata Filtering & Hybrid Search
  • • Day 15 — Reranking & Context Compression
  • • Day 20 — Retrieval Agents
  • • Day 21 — Multi-Agent Design Patterns

Needs deeper validation

  • • Day 4 — How LLMs Work: Tokens & Context (4 attempts)
  • • Day 10 — Retrieval & Matching Engine (4 attempts)
  • • Day 7 — Model Selection & Cost Tradeoffs (2 attempts)
  • • Day 9 — Embeddings & Semantic Similarity (2 attempts)
  • • Day 24 — Human-in-the-Loop Workflows (2 attempts)
  • • Day 25 — Evaluation Metrics for LLM Apps (2 attempts)

Unvalidated (skipped)

  • • Day 1 — AI Engineering Landscape
  • • Day 2 — Python for AI Systems
  • • Day 3 — APIs, Async & Streaming Basics
  • • Day 6 — Structured Outputs & JSON Schema
  • • Day 11 — Vector Databases in Production
  • • Day 13 — RAG Architecture Fundamentals
  • • Day 14 — Query Rewriting & Expansion
  • • Day 16 — Grounding, Citations & Hallucination Control

Skipped missions are explored, not assumed weak.

Recommended interview topics

  • Day 4 — How LLMs Work: Tokens & ContextLLM Fundamentals & Prompting
  • Day 10 — Retrieval & Matching EngineData, Embeddings & Vector Stores
  • Day 7 — Model Selection & Cost TradeoffsLLM Fundamentals & Prompting
  • Day 1 — AI Engineering LandscapeFoundations of AI Engineering
  • Day 2 — Python for AI SystemsFoundations of AI Engineering
  • Day 5 — Prompt Engineering PatternsLLM Fundamentals & Prompting