Best fit
High school and college students who already know basic programming
AI Coding Workflow
Claude Code Master Course
Learn to use Claude Code responsibly for planning, building, testing, debugging, and shipping real software projects.
This course teaches students and builders how to work with Claude Code as an AI coding partner while still owning the architecture, quality, security, and final decisions behind the code.
Starting point
Basic programming experience in JavaScript, Python, or Java is helpful
Session style
One-on-one or small group tutoring
Student outcome
Use Claude Code to plan and execute coding tasks with human oversight
Course Overview
A practical course for modern AI-assisted development
Claude Code is an agentic coding tool from Anthropic that can read a codebase, edit files, run commands, and integrate with development tools. The course turns that power into a disciplined workflow students can understand, review, and control.
Workflow first
Students learn how to plan tasks, define acceptance criteria, review diffs, and keep control of what gets shipped.
Code quality
Sessions emphasize readable code, testing, debugging, refactoring, Git hygiene, and careful verification.
Responsible AI use
Students learn privacy, permissions, citation, academic honesty, and how to avoid blindly accepting generated code.
Portfolio output
The course can culminate in a small web app, automation tool, API project, or polished coding portfolio feature.
Official resources referenced
Student Fit
Who this course is for
- High school and college students who already know basic programming
- Students building coding portfolios, apps, websites, automations, or research tools
- AP Computer Science A, Python, AI/ML, and Advanced Topics in CS students who want modern development workflows
- Parents who want students to use AI tools responsibly instead of shortcutting learning
- Beginners with strong motivation who can start with a guided programming foundation track
Prerequisites
What students should know before starting
- Basic programming experience in JavaScript, Python, or Java is helpful
- Comfort using files, folders, and a code editor is recommended
- Git/GitHub experience is helpful but can be taught inside the course
- Students should be willing to read, test, and explain code instead of only generating it
Curriculum
Claude Code Master Course curriculum
The curriculum moves from setup and prompting into project execution, testing, debugging, Git workflows, safety, and a capstone build.
1
Level 1: Setup and Tooling
Students install and configure the development environment needed for guided Claude Code work.
- Claude Code surfaces
- Terminal basics
- VS Code workflow
- Project folders
- Git setup
- Safe permissions
2
Level 2: Prompting for Code Work
Students learn how to describe tasks clearly enough for useful implementation plans.
- Task briefs
- Acceptance criteria
- Context files
- Constraints
- Follow-up prompts
- Review prompts
3
Level 3: Codebase Navigation
Students practice using AI to understand unfamiliar projects without losing their own understanding.
- Repository maps
- File roles
- Dependency tracing
- Architecture notes
- Read-before-edit habits
- Questioning outputs
4
Level 4: Feature Building
Students build small features through planning, incremental changes, and human review.
- Implementation plans
- Component edits
- API changes
- State handling
- UI polish
- Regression checks
5
Level 5: Testing and Debugging
Students learn to ask Claude Code for tests, interpret failures, and verify fixes.
- Unit tests
- Manual test plans
- Error logs
- Debug loops
- Linting
- Build verification
6
Level 6: Git, Reviews, and Pull Requests
Students learn professional habits for reviewing diffs and preparing changes for sharing.
- Branches
- Commits
- Diff review
- PR descriptions
- Rollback thinking
- Release notes
7
Level 7: Safety and Responsible AI
Students learn where AI coding tools can fail and how to protect privacy, security, and academic integrity.
- Secrets handling
- Private data
- Permission review
- Hallucination checks
- Academic honesty
- Human ownership
8
Level 8: Capstone Project
Students complete a guided project with planning, implementation, testing, review, and presentation.
- Project proposal
- Milestones
- Feature build
- Testing report
- Demo script
- Portfolio write-up
Practice
Hands-on Claude Code labs
Practice is project-based. Students use Claude Code for real development tasks, then explain and verify every important change.
Prompt rewrite drills
Codebase tour
Bug-fix lab
Test-generation lab
Feature build
Diff review
Git workflow
Capstone demo
Outcomes
By the end of this course, students will be able to
- Use Claude Code to plan and execute coding tasks with human oversight
- Write clearer prompts, constraints, and acceptance criteria for software work
- Navigate a codebase and explain what changed after an AI-assisted edit
- Generate and run tests, diagnose errors, and verify fixes
- Use Git habits that support review, rollback, and collaboration
- Build a portfolio-ready project while using AI responsibly
Learning Format
How sessions are structured
- One-on-one or small group tutoring
- Guided live coding
- Project-based labs
- Responsible AI checkpoints
- Code review practice
- Capstone presentation
Why Code Scholars
Support that builds real understanding
Modern Workflow
Students learn how real developers are beginning to use agentic coding tools in practical workflows.
No Blind Copying
Every AI-assisted change is reviewed, tested, and explained so the student keeps ownership.
Portfolio Focus
The course can produce a working project students can discuss with confidence.
Safety First
Students learn permissions, privacy, secrets, and academic honesty before high-autonomy workflows.
Stronger Engineering Habits
Planning, testing, Git, and debugging stay central even when AI helps write code.
Personalized Pace
The course can start from basic setup or move quickly into advanced project workflows.