COURSE CONTENT
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Proposed topic: Git and GitHub for Scripts and Projects — Practical Workbook. This is an interest check; the book is not yet available.
Anonymous interest only. This does not subscribe you to email or reserve a copy.COURSE OVERVIEW
What you will learn
Take a deliberately flawed capacity classifier from a documented failing baseline to a reviewable repair. Learn what Git actually records, preserve unrelated edits, collaborate through a local remote, resolve a scope conflict and recover using new commits. Your final deliverable is a change another operator can inspect and reproduce—not just a repository with a green badge.
Use Git 2.23 or later, Python 3.10 or later and a new local practice directory. The validated environment uses Git 2.51.1 on Linux. Commands use a Bash-style terminal; PowerShell path syntax and some setup commands differ. No real infrastructure, token or GitHub account is required. The offline bare-remote exercise practices Git transport; GitHub account authentication, permissions and branch protections require separate service-specific verification.
You should be comfortable editing a text file and running a Python unittest command. Python Foundations is helpful, but the five-line classifier is explained below. Do not perform recovery experiments in your CogniSkill source, work repository or any directory containing uncommitted real work.
Four chapters, with practical work
- Distinguish your files, the staged snapshot and history
- Repair on a branch and commit what you actually reviewed
- Collaborate, inspect incoming work and resolve a real conflict
- Recover safely and defend the complete change
Applied capability and learning route
Review a narrowly scoped behavioral change with regression evidence.
Follow the lessons in order: establish the model, trace the supplied evidence, attempt the case, compare the worked solution, and complete the changed-condition project. The target is intermediate reasoning within this stated scope, not mastery of the entire profession or product. If a prerequisite is unfamiliar, pause and use the linked foundational teaching before attempting the project.
All teaching, explained answers and core synthetic practice are free. Some operational labs require separately available software, a licensed test tenant or an authorized lab; offline completion does not claim hands-on product proficiency.
How to complete this course
Study the worked examples, attempt the exercises before opening solutions, and submit your own project notes. Completion records are self-reported; practical competence requires the stated verification.
What you will learn
- Repair a documented script defect through reviewed staging, independent clone verification, conflict resolution and visible recovery commits.
- Review a narrowly scoped behavioral change with regression evidence.
Before you start
- Comfort creating a local practice file and following terminal instructions. Begin with the setup and context checks.
Practice environment
- Git 2.23 or later and Python 3.10 or later, in new isolated repositories. The collaboration exercise uses a local bare remote, not an external account.
Tested versions
- See the manuscript and validation record. A successful offline fixture does not validate every operating environment.
Technical review: 2026-10-07
Technical referencePractical project
Repair a documented script defect through reviewed staging, independent clone verification, conflict resolution and visible recovery commits.
Applied transfer project: Use the supplied deliberately broken capacity exercise in a new repository. Record failing output, make the minimal repair and rerun tests. Inspect staged changes before committing. Add a review note explaining the requirement, evidence and remaining assumptions about numeric validation. Then simulate an upstream change to the same function and resolve the conflict by preserving intended behavior and rerunning tests, not by blindly choosing one entire file.
Check your project
- Reproduce the supplied baseline.
- Explain a boundary or negative case.
- Detect and repair a deliberate defect.
- Submit evidence and state unverified limitations.
- Applied laboratory rubric: five dimensions, 0–2 each; target 8/10 with no zero in main result or safety. Native quiz score is separate.
Use these criteria for self-review. Completing a lesson records your progress; it does not verify code correctness.
Practice files
APPLY THE SKILL
Your practical project
Repair a documented script defect through reviewed staging, independent clone verification, conflict resolution and visible recovery commits. Applied transfer project: Use the supplied deliberately broken capacity exercise in a new repository. Record failing output, make the minimal repair and rerun tests. Inspect staged changes before committing. Add a review note explaining the requirement, evidence and remaining assumptions about numeric validation. Then simulate an upstream change to the same function and resolve the conflict by preserving intended behavior and rerunning tests, not by blindly choosing one entire file.
Evidence to keep
- Reproduce the supplied baseline.
- Explain a boundary or negative case.
- Detect and repair a deliberate defect.
- Submit evidence and state unverified limitations.
- Applied laboratory rubric: five dimensions, 0–2 each; target 8/10 with no zero in main result or safety. Native quiz score is separate.
Use fictional practice data. Keep your inputs, outputs and explanation of the result. Lesson completion records your progress; it does not verify your project.
PRACTICE MATERIALS
Course downloads
Save the materials before starting your lab. Read source files before running them.
CHECK YOUR KNOWLEDGE