Practical Workshop: GenAI GitHub Copilot Code Assistant
This intensive intermediate-level training is specifically designed for Ops and System Engineer profiles wishing to make the leap from scripting to AI-assisted development. In a constantly evolving technological ecosystem, GitHub Copilot stands out as an essential lever to accelerate code writing and reduce repetitive, low-value-added tasks. During this practical workshop, you will learn to master this generative AI-based assistant, capable of suggesting code in real-time and adapting to your context. You will discover how to structure your prompts to generate robust Python scripts (logs, metrics) and automate your deployments via Ansible. More than just an autocompletion tool, you will learn to use Copilot as a true partner to refactor, document, and secure your code, while maintaining a critical eye on the provided suggestions.
Ce que vous allez apprendre
- Discover GitHub Copilot, its usage modes (Assistant vs. Agent), and its operation within the IDE.
- Understand the fundamental role of the workspace and context to optimize the relevance of AI suggestions.
- Know how to interact effectively with Copilot to produce, refactor, and document Python and Ansible code.
- Be able to use Copilot autonomously by adopting good verification and security practices right from the end of the training.
Prérequis
- Basic knowledge of the Python language (imports, packages, script structure).
- Understanding of basic Ansible concepts (commands, playbooks, idempotency).
- Basic knowledge of Git (tracking changes) and shell usage.
- Familiarity with containerization concepts (Docker, images, volumes).
- Ability to read logs and execute scripts from the command line.
Public cible
- System engineers and Ops profiles transitioning from scripting to development.
Programme de la Formation
6 modules pour maîtriser les fondamentaux
Sujets abordés
- →Overview of generative AI and definition of a code assistant.
- →Positioning of GitHub Copilot in the ecosystem.
- →Distinction between Assistant (Chat) and Agent (Autonomous) modes.
Activités
Quick Python / Ansible demonstration.
First steps with the interface.
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Prochaines sessions
Aucune date ne vous convient ?
Nous organisons régulièrement de nouvelles sessions. Contactez-nous pour connaître les prochaines dates disponibles ou pour organiser une session à la date de votre choix.
S'inscrire à une date personnaliséeFormer plusieurs collaborateurs
- Tarifs dégressifs (plusieurs places)
- Session privée ou sur-mesure
- En présentiel ou à distance