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Course Outline

Module 1 – Advanced Git & GitHub Workflows

  • Complex Git concepts and advanced repository administration
  • Comparative analysis of branching strategies: GitFlow versus trunk-based development
  • Techniques for rebasing, merging, and cherry-picking
  • Utilizing interactive rebase for history refinement
  • Strategies for managing and resolving intricate merge conflicts
  • Version control through tags, releases, and semantic versioning
  • Investigating Git history and recovering lost work
  • Best practices optimized for large-scale engineering teams

Module 2 – Advanced Pull Requests & Collaboration

  • Architecting efficient pull request pipelines
  • Leveraging draft pull requests and structured review methodologies
  • Implementing CODEOWNERS for automated ownership
  • Configuring branch protection rules and advanced rulesets
  • Enforcing required reviews and status check validations
  • Tactics for handling extensive or long-lived pull requests
  • Standardizing contributions via issue and pull request templates
  • Utilizing GitHub Projects for task tracking
  • Governing teams, permissions, and repository access
  • Practical exercise: Architecting an enterprise-grade collaboration framework

Module 3 – GitHub Actions & CI/CD

  • Understanding the underlying architecture of GitHub Actions
  • Defining workflows, jobs, steps, and event triggers
  • Managing secrets, variables, and deployment environments
  • Implementing conditional logic and managing job dependencies
  • Scaling builds using matrix strategies
  • Optimizing performance through artifacts and caching mechanisms
  • Creating reusable workflows and composite actions for modularity
  • Debugging techniques and performance optimization
  • Constructing robust continuous integration pipelines
  • Automating test suites and build processes
  • Orchestrating multi-environment deployment strategies
  • Automating the release lifecycle
  • Practical exercise: Engineering a complete end-to-end CI/CD pipeline

Module 4 – GitHub Security & Automation

  • Exploring native GitHub security features
  • Leveraging Dependabot for proactive dependency management
  • Integrating dependency review workflows
  • Deploying secret scanning and push protection mechanisms
  • Running code scanning for vulnerability detection
  • Formulating security policies and managing vulnerabilities
  • Hardening the software supply chain
  • Command-line automation using the GitHub CLI
  • Overview of the GitHub REST API
  • Implementing webhooks and third-party integrations
  • Scripting automation for repositories, issues, and pull requests
  • Practical exercises in security hardening and workflow automation

Module 5 – End-to-End GitHub Workflow

  • Designing a holistic GitHub development lifecycle
  • Establishing repository structure and branching policies
  • Refining the pull request and code review cycle
  • Integrating automated testing suites
  • Connecting the CI/CD pipeline
  • Embedding security validation checks
  • Streamlining release management processes
  • Advanced troubleshooting and performance tuning
  • Collaborative team-based practical exercise
  • Course summary and open Q&A session

Optional Module – GitHub Copilot

  • Overview of GitHub Copilot capabilities and workflow integration
  • Using Copilot Chat and IDE extensions
  • Crafting effective prompts for developer productivity
  • Generating and explaining code snippets
  • Assisted refactoring and optimization
  • Automatic unit test generation
  • Debugging assistance using Copilot
  • Automated documentation creation
  • Enhancing pull requests and code reviews with AI
  • Best practices for responsible and secure AI-assisted coding
  • Hands-on exercises with GitHub Copilot

Requirements

To fully benefit from this training, participants are expected to have:

  • Hands-on experience working with Git and GitHub
  • A solid grasp of core concepts such as repositories, branches, commits, and pull requests
  • Foundational knowledge of GitHub Actions, which is advantageous but not mandatory
  • General familiarity with standard software development lifecycles
 14 Hours

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