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Yuki Tanaka

CND-1010 · Data Scientist · 8 yrs · M.Tech Data Science

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Completion

65%

First-try rate

35%

Avg attempts

2.25

Consistency

48%

Curriculum coverage by module

First-attempt mastery signal

Attempts by topic (higher = needs validation)

Strong areas

  • • Day 1 — AI Engineering Landscape
  • • Day 15 — Reranking & Context Compression
  • • Day 17 — Tool Calling Fundamentals
  • • Day 18 — Agent Loops & Planning
  • • Day 19 — Memory & State Management
  • • Day 25 — Evaluation Metrics for LLM Apps

Needs deeper validation

  • • Day 12 — Metadata Filtering & Hybrid Search (4 attempts)
  • • Day 14 — Query Rewriting & Expansion (4 attempts)
  • • Day 21 — Multi-Agent Design Patterns (4 attempts)
  • • Day 26 — LLM-as-a-Judge & Rubrics (4 attempts)
  • • Day 27 — Guardrails, Safety & Prompt Injection (4 attempts)
  • • Day 22 — Multi-Agent Orchestration (3 attempts)

Unvalidated (skipped)

  • • Day 3 — APIs, Async & Streaming Basics
  • • Day 4 — How LLMs Work: Tokens & Context
  • • Day 5 — Prompt Engineering Patterns
  • • Day 8 — Text Chunking Strategies
  • • Day 11 — Vector Databases in Production
  • • Day 13 — RAG Architecture Fundamentals
  • • Day 16 — Grounding, Citations & Hallucination Control
  • • Day 20 — Retrieval Agents

Skipped missions are explored, not assumed weak.

Recommended interview topics

  • Day 12 — Metadata Filtering & Hybrid SearchData, Embeddings & Vector Stores
  • Day 14 — Query Rewriting & ExpansionRetrieval-Augmented Generation
  • Day 21 — Multi-Agent Design PatternsMulti-Agent Orchestration
  • Day 3 — APIs, Async & Streaming BasicsFoundations of AI Engineering
  • Day 4 — How LLMs Work: Tokens & ContextLLM Fundamentals & Prompting
  • Day 1 — AI Engineering LandscapeFoundations of AI Engineering