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

Access provided by Babeş-Bolyai University of Cluj-Napoca

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

Details to know

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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: CI/CD
Category: Model Context Protocol
Category: Agentic systems
Category: Agentic Workflows
Category: Tool Calling
Category: AI Workflows
Category: Generative AI Agents
Category: Code Review
Category: Software Documentation
Category: Issue Tracking
Category: Open Source Technology
Category: Version Control
Category: Continuous Integration
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: Cloud Development
Category: CI/CD
Category: Large Language Modeling
Category: GitHub
Category: Docker (Software)
Category: Fine-tuning
Category: DevOps
Category: Development Environment
Category: Python Programming
Category: Hugging Face
Category: YAML
Category: AI Enablement
Category: Containerization
Category: Model Deployment
Category: AI Personalization
Category: Continuous Deployment
Category: Continuous Integration
Category: AI Workflows
Category: Microsoft Copilot
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: MLOps (Machine Learning Operations)
Category: Enterprise Security
Category: Okta
Category: Package and Software Management
Category: Git (Version Control System)
Category: Single Sign-On (SSO)
Category: CI/CD
Category: Azure Active Directory
Category: Enterprise Application Management
Category: Security Strategy
Category: User Provisioning
Category: Role-Based Access Control (RBAC)
Category: Authorization (Computing)
Category: Automation
Category: Containerization
Category: Apache Maven
Category: Identity and Access Management
Category: Security Assertion Markup Language (SAML)
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: Software Documentation
Category: LLM Application
Category: Generative AI Agents
Category: AI Workflows
Category: Agentic Workflows
Category: Prompt Engineering Tools
Category: GitHub
Category: GitHub Copilot
Category: Prompt Patterns
Category: Context Engineering
Category: Software Development
Category: Context Management
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: Development Testing
Category: Code Review
Category: Test Case
Category: Test Automation
Category: Restful API
Category: AI Workflows
Category: API Testing
Category: GitHub Copilot
Category: GitHub
Category: Application Development
Category: Requirements Analysis
Category: API Design
Category: Business Logic
Category: Software Technical Review
Category: Test Script Development
Category: Application Programming Interface (API)
Category: Software Architecture
Category: Data Integrity
Category: Software Testing
Category: Object-Relational Mapping
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 Copilot
Category: OpenAI API
Category: AI Enablement
Category: Anthropic Claude
Category: Responsible AI
Category: AI Workflows
Category: Verification And Validation
Category: Application Security
Category: Open Web Application Security Project (OWASP)
Category: Generative AI Agents
Category: Generative AI
Category: Model Evaluation
Category: Large Language Modeling
Category: Code Review
Category: GitHub
Category: AI Security
Category: Secure Coding
Category: Vulnerability Scanning
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: Security Controls
Category: Identity and Access Management
Category: GitHub
Category: Multi-Factor Authentication
Category: Systems Administration
Category: Authentications
Category: Authorization (Computing)
Category: Security Engineering
Category: Role-Based Access Control (RBAC)
Category: Collaborative Software
Category: Data Security
Category: Enterprise Application Management
Category: Version Control
Category: Security Management
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: Model Evaluation
Category: Application Programming Interface (API)
Category: Capacity Management
Category: Responsible AI
Category: Microsoft Azure
Category: API Design
Category: Generative AI
Category: Authentications
Category: Cloud Development
Category: GitHub
Category: Data Validation
Category: Model Deployment
Category: AI Integrations
Category: Development Environment
Category: Prompt Engineering
Category: LLM Application
Category: AI Enablement
Category: Scalability
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: Software Testing
Category: Maintainability
Category: Infrastructure as Code (IaC)
Category: Containerization
Category: Test Driven Development (TDD)
Category: Rust (Programming Language)
Category: Style Guides
Category: Test Tools
Category: Other Programming Languages
Category: GitHub
Category: Unit Testing
Category: GitHub Copilot
Category: Terraform
Category: Dependency Analysis
Category: Test Automation
Category: Test Script Development
Category: AI Workflows
Category: AI Integrations
Category: Ansible
Category: Docker (Software)

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Instructors

Noah Gift
Pragmatic AI Labs
43 Courses2,959 learners
Liam Parker
Pragmatic AI Labs
5 Courses801 learners
Alfredo Deza
Pragmatic AI Labs
32 Courses1,390 learners

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