Plan d'action

Le plan d'action du AI

128 actions concrètes distillées des leçons, réparties en 8 catégories. Ouvrez une catégorie, dépliez chaque action pour son mode d'emploi étape par étape, et cochez au fil de l'eau.

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01

AI & LLM foundations

What AI, machine learning, and large language models actually are, how they work at a topline level, and where their capabilities end.

11 actions
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02

Prompt engineering

The practical craft of getting great results: structuring prompts, giving examples, asking for step-by-step reasoning, and iterating fast.

11 actions
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03

AI in daily work

Turning AI into a genuine productivity multiplier for writing, analysis, research, and admin, plus the judgment to know when not to use it.

11 actions
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04

Responsible & trustworthy AI

Using AI safely and ethically: bias, verification, confidential data, copyright, and the topline of AI governance and the EU AI Act.

11 actions
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05

Building with AI

How to structure an AI project, navigate the tools landscape (RAG, agents, vector databases, APIs), write basic code, and evaluate outputs against cost and latency.

14 actions
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06

ChatGPT & the OpenAI ecosystem

A deep, hands-on mastery path for ChatGPT: models and Projects, Custom GPTs, Actions and Connectors, data analysis and multimodal, Codex and Canvas, agents, the OpenAI API, automation, and a capstone.

27 actions
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07

Claude & the Anthropic ecosystem

A deep, hands-on mastery path for Claude: models and Projects, connectors, Skills, MCP, Claude Code, GitHub workflows, the Anthropic API and Agent SDK, automation, and a capstone.

32 actions
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08

Gemini & Google AI

A deep, hands-on mastery path for Gemini: models and the app, Gems, Workspace, Extensions, AI Studio and the Gemini API, Gemini CLI and Code Assist, agents, Vertex AI, automation, and a capstone.

11 actions
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