Pragmatic AI Labs

Mastering GitHub Specialization

Pragmatic AI Labs

Mastering GitHub Specialization

Master GitHub from Git basics to AI agents.

Build production skills across Git, security, Actions, Codespaces, AI models, and agent workflows

Noah Gift
Liam Parker
Alfredo Deza

Instructors: Noah Gift

Included with Coursera Plus

Get in-depth knowledge of a subject
Beginner level

Recommended experience

10 months to complete
at 5 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Beginner level

Recommended experience

10 months to complete
at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Manage and configure GitHub at an enterprise-scale, enabling productivity, security, and fine-grained permissions

  • Automate CI/CD pipelines with GitHub Actions workflows, self-hosted runners, and publish packages through GitHub Packages registries

  • Configure enterprise identity management with SAML SSO, Enterprise Managed Users, and two-factor authentication enforcement across organizations

  • Build cloud development environments with GitHub Codespaces including GPU instances, dev containers, and Copilot integration

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Taught in English
Recently updated!

April 2026

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Specialization - 9 course series

GitHub: From Zero to Pull Request

GitHub: From Zero to Pull Request

Course 1, 2 hours

What you'll learn

Skills you'll gain

Category: Git (Version Control System)
Category: GitHub
Category: AI Workflows
Category: Tool Calling
Category: CI/CD
Category: Open Source Technology
Category: Model Context Protocol
Category: Version Control
Category: Continuous Integration
Category: Agentic Workflows
Category: Agentic systems
Category: Software Documentation
Category: Generative AI Agents
Category: Code Review
Category: Issue Tracking
GitHub: Codespaces, Actions, and Ecosystem Tools

GitHub: Codespaces, Actions, and Ecosystem Tools

Course 2, 2 hours

What you'll learn

  • Launch and configure GitHub Codespaces with dev containers, including GPU-enabled instances for AI workloads like Whisper transcription

  • Use GitHub Copilot and Copilot Labs for AI-assisted code generation, code translation, and conversational development with Copilot Chat

  • Build GitHub Actions CI/CD workflows using YAML configuration files to automate testing and deployment on containers

Skills you'll gain

Category: GitHub Copilot
Category: CI/CD
Category: Cloud Development
Category: Continuous Integration
Category: Large Language Modeling
Category: Containerization
Category: DevOps
Category: GitHub
Category: Docker (Software)
Category: YAML
Category: Microsoft Copilot
Category: AI Enablement
Category: AI Personalization
Category: Fine-tuning
Category: Hugging Face
Category: Continuous Deployment
Category: Python Programming
Category: AI Workflows
Category: Development Environment
Category: Model Deployment
GitHub Enterprise Administration

GitHub Enterprise Administration

Course 3, 4 hours

What you'll learn

  • Configure enterprise identity management with SAML SSO, Enterprise Managed Users, two-factor authentication, and the principle of least privilege

  • Manage repository security using the security tab, dependency graphs, Dependabot alerts, and hierarchical feature controls

  • Automate enterprise workflows with GitHub Actions API, self-hosted runners, and GitHub Packages registries

Skills you'll gain

Category: GitHub
Category: Continuous Integration
Category: Git (Version Control System)
Category: Role-Based Access Control (RBAC)
Category: Apache Maven
Category: Enterprise Security
Category: Authorization (Computing)
Category: Azure Active Directory
Category: Security Assertion Markup Language (SAML)
Category: Automation
Category: Okta
Category: User Provisioning
Category: Identity and Access Management
Category: Containerization
Category: MLOps (Machine Learning Operations)
Category: Enterprise Application Management
Category: CI/CD
Category: Single Sign-On (SSO)
Category: Security Strategy
Category: Package and Software Management
GitHub: Advanced Prompt Engineering for Code

GitHub: Advanced Prompt Engineering for Code

Course 4, 3 hours

What you'll learn

  • Structure multi-turn GitHub Copilot conversations that build context incrementally and produce more accurate code than single-shot prompts

  • Apply iterative refinement techniques like scope narrowing, error correction, and follow-up prompting to transform code into production-ready output

  • Leverage cross-file context, open editor tabs, and specification-driven generation to work effectively across large and unfamiliar codebases

Skills you'll gain

Category: Prompt Engineering
Category: Prompt Engineering Tools
Category: GitHub
Category: Software Development
Category: Context Management
Category: GitHub Copilot
Category: Prompt Patterns
Category: Agentic Workflows
Category: Context Engineering
Category: LLM Application
Category: Software Documentation
Category: Generative AI Agents
GitHub Production Applications

GitHub Production Applications

Course 5, 3 hours

What you'll learn

  • Implement a multi-layer production application (API, business logic, data layer) using GitHub Copilot for AI-assisted development

  • Build comprehensive test suites with unit, integration, and end-to-end testing strategies using Makefile-driven quality pipelines

  • Evaluate AI-generated code against industry best practices through structured review and reflection workflows

Skills you'll gain

Category: Code Review
Category: Development Testing
Category: Requirements Analysis
Category: Test Script Development
Category: GitHub Copilot
Category: Restful API
Category: Software Testing
Category: Test Case
Category: Data Integrity
Category: Application Development
Category: GitHub
Category: Software Technical Review
Category: Software Architecture
Category: Test Automation
Category: Application Programming Interface (API)
Category: API Design
Category: AI Workflows
Category: Business Logic
Category: Object-Relational Mapping
Category: API Testing
GitHub: Governing AI-Generated Code

GitHub: Governing AI-Generated Code

Course 6, 4 hours

What you'll learn

  • Apply techniques including static analysis and security scanning to audit AI-generated code for vulnerabilities, flaws, and hallucinations

  • Create custom Copilot configurations using instructions to enforce team coding standards and project-specific conventions across all generated code

  • Evaluate LLM capabilities, performance benchmarks, and cost-benefit trade-offs to select the right model for specific development tasks

Skills you'll gain

Category: Security Testing
Category: LLM Application
Category: GitHub
Category: Model Evaluation
Category: Generative AI
Category: AI Enablement
Category: AI Workflows
Category: OpenAI API
Category: Large Language Modeling
Category: Vulnerability Scanning
Category: GitHub Copilot
Category: Generative AI Agents
Category: Application Security
Category: Code Review
Category: AI Security
Category: Verification And Validation
Category: Open Web Application Security Project (OWASP)
Category: Anthropic Claude
Category: Responsible AI
Category: Secure Coding
GitHub: Security, Identity, and Access

GitHub: Security, Identity, and Access

Course 7, 3 hours

What you'll learn

  • Configure two-factor authentication, permissions, and visibility settings securing accounts and repositories following least-privilege principles

  • Set up enterprise managed users with identity providers and SCIM provisioning for centralized organizational identity control

  • Use the Security tab, Dependabot, repository insights, and team-based roles to monitor and govern GitHub organizations at enterprise scale

Skills you'll gain

Category: Identity and Access Management
Category: GitHub
Category: Security Controls
Category: Role-Based Access Control (RBAC)
Category: Security Management
Category: Authentications
Category: Systems Administration
Category: Version Control
Category: Collaborative Software
Category: Security Engineering
Category: Multi-Factor Authentication
Category: Authorization (Computing)
Category: Enterprise Application Management
Category: Data Security
GitHub: Evaluating and Integrating AI Models

GitHub: Evaluating and Integrating AI Models

Course 8, 5 hours

What you'll learn

  • Navigate the GitHub Models marketplace to evaluate and select AI models based on provider capabilities, rate limits, and responsible AI features

  • Configure GitHub Codespaces development environments and manage scaling from the free tier to Azure AI pay-as-you-go for production workloads

  • Build, test, and validate HTTP API endpoints using FastAPI that integrate AI models from GitHub Models within Codespaces

Skills you'll gain

Category: Application Programming Interface (API)
Category: Model Evaluation
Category: Data Validation
Category: Capacity Management
Category: LLM Application
Category: Generative AI
Category: API Design
Category: AI Enablement
Category: Prompt Engineering
Category: Responsible AI
Category: Model Deployment
Category: Microsoft Azure
Category: Development Environment
Category: Scalability
Category: Cloud Development
Category: AI Integrations
Category: GitHub
Category: Authentications
GitHub: AI-Augmented Testing and Refactoring

GitHub: AI-Augmented Testing and Refactoring

Course 9, 3 hours

What you'll learn

  • Apply AI-assisted test-driven development to generate tests, mock dependencies, and evaluate test coverage using GitHub Copilot and PyTest

  • Analyze cross-file dependencies and execute system-wide code cleanup by leveraging @workspace references and style enforcement with GitHub Copilot

  • Create infrastructure-as-code configurations including Ansible playbooks, Dockerfiles, and Terraform modules using AI-assisted generation workflows

Skills you'll gain

Category: Infrastructure as Code (IaC)
Category: Maintainability
Category: Software Testing
Category: AI Integrations
Category: Test Driven Development (TDD)
Category: Unit Testing
Category: AI Workflows
Category: GitHub
Category: Terraform
Category: Test Automation
Category: Dependency Analysis
Category: GitHub Copilot
Category: Style Guides
Category: Ansible
Category: Test Script Development
Category: Docker (Software)
Category: Rust (Programming Language)
Category: Other Programming Languages
Category: Containerization
Category: Test Tools

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Instructors

Noah Gift
Pragmatic AI Labs
48 Courses3,456 learners
Liam Parker
Pragmatic AI Labs
5 Courses942 learners
Alfredo Deza
Pragmatic AI Labs
33 Courses1,677 learners

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