Professional Developer Workflow for AI
Train production-ready habits for AI builders: professional editor/terminal workflows (VS Code/Cursor), Git/GitHub collaboration, canonical project architecture, configuration & secrets, logging, debugging, testing fundamentals, documentation, AI-assisted coding norms, and a reusable AI repo template portfolio project. `publish_targets: BOTH` — single educational source; branding via overlays.
- Niveau ·
- Anfänger
- 10 Std.
- Module ·
- 4
- Lektionen ·
- 21
- Preis
- Kostenlos
Lehrplan
Nur Modul- und Lektionstitel. Der vollständige Inhalt wird nach der Einschreibung freigeschaltet.
Professional Environment & Editor Fluency
- Professional AI Workspace Overview
- VS Code / Cursor Setup for AI Repos
- Integrated Terminal, Tasks, and Extensions that Matter
- Debugging Basics & Safe AI-Assisted Coding Norms
- M01 Wrap — Professional Environment & Editor Fluency
Git & GitHub Collaboration
- Git Fundamentals: init, status, add, commit, log
- Branching, Pull Requests & GitHub Collaboration
- .gitignore for Python/AI Projects
- What Never to Commit & Leak Remediation
- M02 Wrap — Git & GitHub Collaboration
Architecture, Config, Quality
- Canonical Folder Layout & Reusable Architecture
- Configuration Management & Secrets in Projects
- Logging & Error-Handling Habits in Projects
- Testing Fundamentals & Documentation Quality
- M03 Wrap — Architecture, Config, Quality
Maintainable Delivery & Release
- Task Runners & scripts/ for Maintainable Work
- Pre-commit Mindset & Secret Scanners
- Code Review Checklist for AI Apps
- Tags, Releases & Ship the AI Repo Template
- M04 Wrap — Maintainable Delivery & Release
- JP-JA03 — AI Repo Template