Work You Can Explain
Practical AI, computing, and learning for students
term
Understand the development environment, practice a repeatable programming loop, and use Git as an observable project history.
Use this path when setting up coursework, learning the development toolchain, or building dependable Git habits.
Use the ordered guides as a recommended route. Begin with the first guide for a systematic introduction, or enter where your current task begins and follow prerequisite links as needed.
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Learn the major parts of a programming toolchain, including Git when a course uses it, and identify which component owns a problem.
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Build a course-compatible programming environment without adding conflicting global tools or undocumented dependencies.
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Work from the project root so source, configuration, dependencies, tests, documentation, and terminal commands stay in context.
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Use an understand–plan–change–run–test–checkpoint loop that works with Git or a course's required submission method.
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Build a correct mental model of the Git repository, working tree, staging area, and committed history.
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Inspect untracked, modified, staged, and unstaged changes before committing or accepting an AI edit.
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Create a small verified Git checkpoint with one logical change and a descriptive message.
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Understand how GitHub adds remotes, issues, pull requests, review, access, and project context around Git repositories.
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Create and resolve a controlled Git merge conflict in a disposable repository so the real event is understandable.
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Write a project README that explains purpose, requirements, installation, running, testing, and verification.
