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Academy · 16 lessons · GitHub + AI + DevOps

GitHub AI Engineering Academy

Master GitHub, GitHub Copilot, AI agents, GitHub Actions, and AI-powered DevOps automation.

GitHub is evolving beyond source control into a platform for AI-assisted development and automated software delivery. This academy teaches engineers how to use it that way — from Copilot and GitHub Actions to AI agents and an end-to-end AI-powered DevOps pipeline.

Start with Part 1 → See the full curriculum

For developers, DevOps, platform, cloud, SRE, and AI engineers who already know their way around Git and the command line.

The path

How the academy builds

GitHub Fundamentals
        |
    GitHub Copilot
        |
Infrastructure & Containers
        |
    GitHub Actions
        |
   AI Applications
        |
      AI Agents
        |
Automated AI Code Review
        |
AI-Powered DevOps Pipeline

Each stage builds on the last, ending with an agentic pipeline: Issue → AI Agent → Branch → Code → Tests → Pull Request → AI Review → Human Approval → Deploy.

What you'll learn

GitHub, AI, and DevOps — converging

  • GitHub as a control plane

    Coordinate code, prompts, infrastructure, tests, and deployment in one place.

  • GitHub Copilot for DevOps

    AI-assisted Bash, Docker, Terraform, Kubernetes, Python, and Actions.

  • GitHub Actions

    Automate testing, builds, security scanning, and deployment of AI apps.

  • AI applications

    Ship LLM applications with pipelines, secrets, and environments.

  • AI agents

    Wire agents to issues, branches, and pull requests — with human approval.

  • Automated code review

    Use AI to assist pull-request review without rubber-stamping production.

  • GPU workflows

    Support GPU AI workloads with self-hosted, ephemeral, isolated runners.

  • AI-powered pipeline

    The capstone: an end-to-end Issue → Agent → PR → Review → Deploy flow.

The roadmap

The 16-part curriculum

  1. Part 01Available

    GitHub for AI Engineers

    Use GitHub as the control plane for AI engineering — repos, branches, pull requests, issues, Actions, secrets, APIs, Copilot, and Models around your Python/LLM/infrastructure code.

    BeginnerFoundationsStart lesson
  2. Part 02Available

    GitHub Copilot for DevOps Engineers

    Practical GitHub Copilot for Bash, Docker, Compose, Terraform, Kubernetes, Ansible, Python, and GitHub Actions — with a prompt library and a review-before-you-ship safety workflow.

    BeginnerCopilotStart lesson
  3. Part 03Available

    GitHub Copilot CLI

    AI-assisted terminal workflows with the agentic Copilot CLI — generate, explain, and troubleshoot Git, Docker, Kubernetes, and Terraform commands with approval-gated safety.

    BeginnerCopilotStart lesson
  4. Part 04Available

    GitHub Copilot with VS Code

    The AI-assisted editor: inline completions, Copilot Chat (Ask/Edit/Agent), refactoring, workspace context, and generating and validating DevOps files without leaving your IDE.

    BeginnerCopilotStart lesson
  5. Part 05Available

    GitHub Copilot with Terraform

    AI-assisted Infrastructure as Code — providers, modules, variables, outputs — and how to fmt, validate, lint, security-scan, and plan before anything touches real infrastructure.

    IntermediateCopilot · IaCStart lesson
  6. Part 06Available

    GitHub Copilot with Docker

    Dockerfiles, multi-stage builds, Compose, image optimization, health checks, and security hardening — with Copilot as an accelerator you still build, scan, and review.

    IntermediateCopilot · ContainersStart lesson
  7. Part 07Available

    GitHub Copilot with Kubernetes

    Generate and troubleshoot Kubernetes YAML — Deployments, Services, probes, resource limits, RBAC, Helm — validate with schema/policy checks, and catch the mistakes AI commonly makes.

    IntermediateCopilot · ContainersStart lesson
  8. Part 08Available

    GitHub Copilot for Bash

    Shell automation with Copilot — strict mode, quoting, functions, jq, curl, log parsing, traps — validated with ShellCheck and written safely, never blindly run.

    BeginnerCopilotStart lesson
  9. Part 09Available

    GitHub Copilot for Python

    Python for DevOps and AI automation — REST APIs, JSON/YAML, subprocess safety, type hints, logging, CLIs, AI SDK integration, pytest, and GitHub Actions CI — reviewed, tested, and secured.

    IntermediateCopilotStart lesson
  10. Part 10Available

    GitHub Actions for AI Applications

    CI/CD for AI apps with GitHub Actions — deterministic tests vs AI evaluations, model-provider secrets, workflow security, Docker builds + scanning, staging, human approval, and deployment.

    AdvancedGitHub ActionsStart lesson
  11. Part 11Available

    Building AI Agents with GitHub

    Build an AI agent that turns Issues into pull requests — GitHub API, GitHub Apps, webhooks, constrained tools, least-privilege permissions, sandboxing, prompt-injection defense, and the PR as the human boundary.

    AdvancedAI AgentsStart lesson
  12. Part 12Available

    Deploying LLM Applications Using GitHub Actions

    A production LLM deployment pipeline — Python app, prompt versioning, AI evaluations, Docker + GHCR, Kubernetes, OIDC, staging, smoke tests, human approval, build-once-promote, rollback, and observability.

    AdvancedGitHub ActionsStart lesson
  13. Part 13Coming Soon

    GitHub Models Tutorial

    Experiment with models in GitHub — prompts, comparison, evaluation concepts, and wiring a model into an application, with responsible-use guardrails.

    IntermediateAI ApplicationsIn production
  14. Part 14Coming Soon

    GitHub Actions GPU Workflows

    Support GPU AI workloads from GitHub automation — self-hosted NVIDIA/CUDA runners, containerized GPU jobs, ephemeral runners, isolation, security, and cost.

    AdvancedActions · GPUIn production
  15. Part 15Coming Soon

    Automated AI Code Review

    AI-assisted pull-request review — diffs, static analysis, security scanning, summaries, and risk detection that helps reviewers rather than approving for them.

    AdvancedAI AgentsIn production
  16. Part 16Coming Soon

    Building an AI-Powered DevOps Pipeline

    The capstone: Issue → AI Agent → Branch → Code → Tests → Pull Request → AI Review → Human Approval → Deployment, wiring together everything the academy taught.

    AdvancedCapstoneIn production
Optional resources

Recommended GitHub reading

Optional references. The lessons are the primary learning path.

Recommended GitHub Books

Affiliate Disclosure: Some links on this page are affiliate links. If you purchase through one of these links, DevOps AI Toolkit may earn a commission at no additional cost to you. See our affiliate disclosure.

FAQ

GitHub AI Academy — common questions

Who is the GitHub AI Engineering Academy for?

Developers, DevOps and platform engineers, SREs, infrastructure engineers, and AI engineers who want to use GitHub — repos, Actions, Copilot, Models, and agents — as the control center for AI-assisted software development and DevOps automation. It is not a generic Git beginner course.

Is this a beginner Git or GitHub course?

No. It assumes you can use Git and the command line. The theme is GitHub + AI + DevOps + automation: how GitHub coordinates AI-assisted coding, CI/CD, infrastructure, containers, and AI agents — leading to an end-to-end AI-powered DevOps pipeline.

Do I need GitHub Copilot to follow along?

The concepts stand on their own, but the Copilot lessons are most useful if you have access to GitHub Copilot. Where a feature is a paid or rapidly changing product, the lessons say so and point you to the current official GitHub documentation.

Does the academy teach that AI can replace engineering review?

No — the opposite. A recurring principle across every lesson is that AI-generated code and infrastructure must be reviewed, validated, scanned, tested, and human-approved before production. AI assists engineers; it does not replace judgment.

How many lessons are there, and which are available now?

Sixteen lessons, from GitHub fundamentals for AI engineers through the capstone AI-powered DevOps pipeline. Parts 1 and 2 are available now; Parts 3–16 are on the published roadmap and released over time.

Are GitHub Copilot and GitHub Models details kept current?

GitHub AI features evolve quickly. Stable Git and GitHub concepts are taught directly; rapidly changing product details (Copilot CLI, agents, Models, model names) are described at a conceptual level and flagged to verify against current GitHub documentation before you rely on exact commands.

Start using GitHub as your AI engineering control plane

Begin with the foundations, then bring Copilot, GitHub Actions, and AI agents into a modern AI-powered DevOps workflow.

Start Part 1: GitHub for AI Engineers →