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Claude Code Masterclass Ship Real Code With Ai

Claude Code Masterclass: Ship Real Code With Ai
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 788.82 MB | Duration: 1h 45m
Install Claude Code and master the Plan → Implement → Test → Review → Commit loop: Best-of-N, testing, git, MCP, hooks &
What you'll learn
Install, configure, and run Claude Code on macOS, Linux, or Windows (WSL2), and pick the right model - Opus, Sonnet, or Haiku - for each task
Master the Plan → Implement → Test → Review → Commit loop and apply it to every change so AI-generated bugs never reach production.
Use Best-of-N, rubric scoring, and the "stranger's PR" self-review prompt to ship code chosen on evidence, not a gut feeling
Run professional git workflows, connect the GitHub MCP server, and automate guardrails with hooks, skills, and CLAUDEmd brain files
Requirements


Basic programming familiarity (any language) and comfort using a terminal.
A computer running macOS, Linux, or Windows with WSL2, and a paid Claude account (Pro, Max, Team, or Enterprise) - the free web plan does not include Claude Code
No prior AI-tooling experience required; Python 3.11+ is used for the example project but you don't need to be a Python expert.
Description
Stop treating AI like a magic autocomplete and start using it like a sharpjunior engineer who sits next to you - one you direct, review, and holdaccountable. The Claude Code Masterclass teaches you the exact workflowprofessional developers use to ship real, tested code with Anthropic'sClaude Code, the agentic command-line coding tool.You'll begin by installing and configuring Claude Code on macOS, Linux, orWindows (WSL2), then internalize the single loop that runs through everymodule: **Plan → Implement → Test → Review → Commit**. From there, eachhands-on module builds a piece of a real project so the techniques stick.What you'll practice, live, in the terminal:- Prompting that reads like a well-written ticket, not a wish.- CLAUDEmd brain files so Claude follows your project's conventions.- Best-of-N - generate independent candidates, score them on a rubric, and ship the winner with evidence instead of a gut feeling.- Testing & debugging - generate honest test suites and use the "stranger's PR" self-review prompt to make Claude find its own bugs.- Git workflows - atomic commits, Conventional Commits, and pull requests written from the diff, never the prompt.- Multimodal work, refactoring & docs, reusable skills, the GitHub MCP server, lifecycle hooks, and a production-readiness checklist.Throughout, you stay the engineer of record - Claude proposes, you decidewhat ships. You'll never let it push to main, and you'll never skip review.By the end you'll own a repeatable, defensible AI coding workflow you cantake straight into your day job.Whether you're a working developer adding AI to your toolkit or a learnerwho wants to build software faster without sacrificing quality, this coursegives you the discipline and the muscle memory to do it right.
orking developers and engineers who want to add AI coding to their daily workflow without sacrificing code quality, plus motivated learners and students who want to build real, tested software faster,Ideal for anyone who wants a disciplined, repeatable way to direct an AI coding agent - and stay the engineer of record who decides what ships


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