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Coursera

GitHub: Codespaces, Actions, and Ecosystem Tools

Pragmatic AI Labs via Coursera

Overview

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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.

Syllabus

  • Codespaces and Development Environments
    • Covers Codespaces, GPU instances, Copilot, template, and repository.
  • Ecosystem Integration and Workflows
    • Covers Codespaces, Copilot, and GitHub Actions.
  • Capstone Project
    • Apply Codespaces, Copilot, and GitHub Actions concepts in an end-to-end project integrating cloud development environments, AI-assisted coding, and CI/CD automation.

Taught by

Noah Gift

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