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