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.

Claude Code Master Course student learning

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

These links are useful for official course, exam, credential, or platform details.

Student Fit

Who this course is for

The starting point is adjusted to the student's age, coding background, school workload, and long-term goals.

  • 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

A bridge track is available when a student needs foundations before the main curriculum.

  • 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

Students get direct coaching, careful correction, and a course path that turns practice into visible progress.

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.

Start Claude Code Master Course

Schedule a consultation to discuss current level, goals, timeline, and the best starting point.