AI curriculum
Course outline for AI-Assisted Software Development
Generated code still needs engineering judgment. Use AI assistance across a small change while keeping requirements, reviews, and tests under developer control.
About AI-Assisted Software Development
Generated code still needs engineering judgment. Use AI assistance across a small change while keeping requirements, reviews, and tests under developer control.
AI-Assisted Software Development Course Objectives
- Translate requirements into a reviewable change plan.
- Inspect and revise generated code.
- Verify a change with tests and updated documentation.
Pre-requisites
- Programming experience and basic version control skills.
- Ability to run tests in a small repository.
Lab Setup
- Computer with Git, a code editor, and a testable sample repository.
- Local AI tooling or supplied generated patches; optional service accounts must be nonproduction.
Detailed Course Outline
Proposed modulesModule 1: Planning changes
- AI-assisted requirements analysis
- AI-assisted architecture
- Code generation
Practical outcome: Draft acceptance criteria and a bounded implementation plan.
Module 2: Inspecting implementation
- Code review
- Refactoring
- Debugging
Practical outcome: Review generated changes and investigate a defect.
Module 3: Verifying repository changes
- Testing
- Documentation
- Repository understanding
Practical outcome: Connect test evidence and documentation to affected code.
Practical exercise
- Complete a small repository change with AI assistance and produce a reviewed diff and test report.
How we train
Contact us for full course details, including duration, delivery options and lab requirements.
Ask about exercises, instructor feedback and the prior knowledge you need. Tool-specific courses marked provisional may become modules in a broader course.
Discuss your learning goals