Module 1 | Requirement Analysis  (Week 1)

Translate a vague product idea into a clear, buildable specification.

•     Discovering stakeholder needs and writing user stories

•     Functional vs. non-functional requirements

•     Using AI (Claude/ChatGPT) to interrogate and stress-test a product idea

•     Turning requirements into an MVP feature list and acceptance criteria

AI / Tools: Claude, ChatGPT, Notion / Miro

Deliverable: A one-page Product Requirements Document (PRD) for the capstone project

Module 2 | AI Prompt Engineering  (Week 2)

Direct AI tools reliably so they produce production-usable output on the first or second try.

•     Prompt anatomy: role, context, constraints, output format

•     Few-shot examples, chain-of-thought, and self-critique prompting

•     Context engineering for long, multi-file coding sessions

•     Building reusable prompt templates for recurring dev tasks

AI / Tools: Claude, system prompts, prompt libraries

Deliverable: A personal prompt-template library for requirements, code, and tests

Module 3 | UI Generation  (Week 3)

Design and generate a usable interface without a dedicated designer.

•     Wireframing from requirements

•     AI-assisted UI generation (Claude Artifacts, v0, Figma AI)

•     Component-based design systems and responsive layout

•     Refining AI-generated UI for accessibility and brand consistency

AI / Tools: Claude Artifacts, v0, Figma, Tailwind CSS

Deliverable: A clickable UI prototype for the capstone application

Module 4 | Database Design  (Week 4)

Model data correctly before writing a single line of backend code.

•     Entity-relationship modelling and normalization

•     Choosing SQL vs. NoSQL for a given use case

•     AI-assisted schema generation and query drafting

•     Indexing, constraints, and seed data for local development

AI / Tools: PostgreSQL / MongoDB, dbdiagram.io, Claude

Deliverable: A finalized ER diagram and schema migration script

Module 5 | API Development  (Week 5)

Build a clean, well-documented backend that the UI can talk to.

•     REST API design principles and versioning

•     Authentication, authorization, and input validation

•     AI-assisted endpoint scaffolding and error handling

•     API contracts and OpenAPI/Swagger documentation

AI / Tools: Node.js / Express or FastAPI, Postman, Claude

Deliverable: A working, documented API with core CRUD endpoints

Module 6 | AI-Assisted Coding  (Week 6)

Pair-program with AI to ship features faster without losing code quality.

•     Working with AI coding agents (Claude Code, Cursor, Copilot)

•     Task decomposition: breaking features into AI-sized steps

•     Code review habits when AI writes the first draft

•     Refactoring and maintaining architectural consistency

AI / Tools: Claude Code, VS Code / Cursor, Git

Deliverable: Core application features implemented end-to-end

Module 7 | Testing with AI  (Week 7)

Catch bugs before users do, using AI to widen test coverage quickly.

•     Unit, integration, and end-to-end testing fundamentals

•     AI-generated test cases and edge-case discovery

•     Debugging strategies when working with AI-written code

•     Continuous testing in the development workflow

AI / Tools: Jest / Pytest, Playwright, Claude

Deliverable: A test suite covering critical application paths

Module 8 | Deployment  (Week 8)

Ship the project to a live, publicly accessible environment.

•     Environment management and configuration secrets

•     Containerization basics with Docker

•     CI/CD pipelines for automated build and deploy

•     Hosting on cloud platforms (Vercel, Render, AWS/GCP)

AI / Tools: Docker, GitHub Actions, Vercel / Render

Deliverable: A live, publicly accessible deployment of the capstone project

Module 9 | Documentation  (Week 9)

Communicate the project clearly to future developers, reviewers, and recruiters.

•     Writing effective READMEs and setup guides

•     API and codebase documentation with AI assistance

•     Architecture diagrams and decision records

•     Writing a project case study for a portfolio

AI / Tools: Markdown, Claude, diagram tools

Deliverable: Complete project documentation and architecture overview

Module 10 | GitHub Portfolio  (Week 10)

Package all coursework into a portfolio that gets interviews.

•     Structuring a GitHub profile that recruiters trust

•     Commit hygiene, branching, and pull request practice

•     Writing a standout portfolio README and pinned repos

•     Final capstone presentation and peer review

AI / Tools: GitHub, GitHub Pages / personal site

Deliverable: A published GitHub portfolio featuring the capstone project