Learn to build cloud-based development environments with GitHub Codespaces, run GPU-accelerated AI workloads, use GitHub Copilot for AI-assisted coding, and automate CI/CD pipelines with GitHub Actions. This hands-on course walks you through launching Codespaces from repository templates, configuring dev containers for different machine types, and running NVIDIA GPU instances for machine learning tasks. You will use Whisper for speech-to-text transcription on GPU-enabled Codespaces and explore Hugging Face for model hosting, datasets, and fine-tuning pre-trained models. The course demonstrates GitHub Copilot and Copilot Labs for code suggestions, code translation, and conversational development via Copilot Chat. You will also build GitHub Actions workflows using YAML configuration files to automate testing and deployment on Ubuntu containers. By the end, you will integrate Codespaces, Copilot, and Actions into a unified end-to-end development workflow. Each lesson includes live demonstrations inside real GitHub repositories, giving you practical experience with the tools used in professional software teams.

GitHub: Codespaces, Actions, and Ecosystem Tools

Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
3 hours to complete
Flexible schedule
Learn at your own pace
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
Details to know

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Recently updated!
March 2026
Assessments
3 assignments
Taught in English
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There are 3 modules in this course
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