Engineering/Courses/Catalog/Claude from Zero to Mastery (Claude Certified Architect prep)/5.5 Human review and calibration
BeginnerLesson 41 of 4710 min · hands-on
5.5 Human review and calibration
Part of the Claude from Zero to Mastery (Claude Certified Architect prep) course
Before this: Lesson 4.3 (structured output) and Lesson 4.4 (validation).
The data extraction system is 97% accurate and everyone wants to cut back human review. How do you find out whether that number really allows it? ...
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Start this lesson5.5 Human review and calibrationWhat you'll learn
- The story: a 97% that hid bad news
- A worked example (made up, for illustration only)
- Confidence scores and calibration
- Why do we sample high-confidence cases too?
- How does the review queue work?
- Why are the other ways wrong?
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All lessons in this course
47 lessons- 10.1 What is Claude, really?10 min
- 20.2 How programs talk to Claude10 min
- 30.3 Tokens and the context window: the model's short-term memory10 min
- 40.4 Prompts: how to ask the model for work10 min
- 50.5 Tools: how a model with no hands gets things done10 min
- 60.6 What an agent is, and why a loop comes into it10 min
- 70.7 A map of the Claude family: models, API, Claude Code, SDK and MCP10 min
- 81.0 Introduction: why agents break in practice10 min
- 91.1 The agentic loop10 min
- 101.2 The coordinator and subagent pattern10 min
- 111.3 Building a subagent and giving it context15 min
- 121.4 Enforcing in code, and handoff15 min
- 131.5 Hooks in the Agent SDK15 min
- 141.6 Breaking work down: fixed chains versus dynamic splitting10 min
- 151.7 Sessions: continue, resume and fork10 min
- 162.0 Introduction: a tool is the model's user interface10 min
- 172.1 Tool descriptions and boundaries10 min
- 182.2 Structured errors in MCP10 min
- 192.3 Distributing tools, and tool_choice15 min
- 202.4 Connecting MCP15 min
- 212.5 Choosing the built-in tools10 min
- 223.0 Introduction: how Claude Code learns what your project is like10 min
- 233.1 The CLAUDE.md hierarchy10 min
- 243.2 Commands and skills10 min
- 253.3 Path-specific rules10 min
- 263.4 Plan mode or direct execution10 min
- 273.5 Iterative refinement10 min
- 283.6 Claude Code in CI10 min
- 294.0 Introduction: from "a good answer" to "output you can rely on"10 min
- 304.1 Explicit criteria to cut false positives10 min
- 314.2 Few-shot10 min
- 324.3 Tool use and JSON schema15 min
- 334.4 Validation and retries10 min
- 344.5 Message Batches10 min
- 354.6 Multi-instance and multi-pass review10 min
- 365.0 Introduction: a system that behaves well on a bad day too10 min
- 375.1 Keeping facts in a long conversation15 min
- 385.2 When to escalate to a human10 min
- 395.3 Error propagation in a multi-agent system10 min
- 405.4 Exploring a large codebase10 min
- 415.5 Human review and calibration10 min
- 425.6 Provenance and uncertainty10 min
- 43Wrap-up: the exam's six scenarios10 min
- 44The logic of the answers: eight rules10 min
- 45The exam versus today10 min
- 46Glossary10 min
- 47The exam itself and its conditions10 min
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