AI Driven Development Using GitHub Copilot

Course Description

SkillDynamo’s AI Driven Development Using GitHub Copilot course develops practical, role-relevant capability in AI-driven software development with GitHub Copilot across planning, coding, APIs, tests, debugging, refactoring, documentation, collaboration, security, and delivery. The learning path progresses from essential concepts and planning to implementation, validation, troubleshooting, and operational use.

Learners work through realistic scenarios, guided demonstrations, applied exercises, and evidence-based reviews. Each topic is connected to workplace responsibilities, common risks, quality controls, and measurable outcomes.

The content is independently written for SkillDynamo using the supplied source page as the title, update-date, and topic-alignment reference. Learners finish with an applied scenario and a prioritized improvement plan.

What You Will Learn

• Integrate GitHub Copilot into requirements, design, task decomposition, repository exploration, coding standards, and responsible AI practices
• Manage context through files, symbols, instructions, prompts, examples, constraints, and acceptance criteria
• Generate and review user interfaces, services, APIs, data models, queries, validation, error handling, and integration code
• Compare implementation options, use framework conventions, preserve architecture, and document dependencies and assumptions
• Generate tests, fixtures, mocks, boundary scenarios, debugging hypotheses, logs, and root-cause investigation plans
• Refactor safely, identify vulnerabilities, review secrets and dependencies, assess performance, and validate quality
• Use Copilot for issues, pull requests, code reviews, release notes, onboarding, documentation, and CI/CD workflow assistance
• Establish review controls, governance, metrics, training, team standards, and an adoption improvement roadmap

SkillDynamo Training Approach

SkillDynamo delivers this AI Driven Development Using GitHub Copilot course through instructor-led demonstrations, hands-on exercises, scenario analysis, validation checklists, structured troubleshooting, evidence-based reviews, and a final improvement plan linked to practical workplace outcomes.