IA générative - Avancé - EN

Formation créée le 14/05/2025.
Version du programme : 1

Type de formation

Formation présentielle

Durée de formation

14 heures (2 jours)

IA générative - Avancé - EN


Training Objective : Use generative AI in a professional, high-performance, and secure way to automate workflows, build custom business assistants, and integrate generative AI into operational systems with appropriate governance.

Objectifs de la formation

  • Design dynamic, modular, and high-precision prompts,
  • Build a specialized conversational AI agent contextualized to business needs,
  • Develop micro AI tools using low-code connectors (Make, Zapier, Notion AI, etc.),
  • Manage the quality, traceability, risks, and accountability of AI-generated content,
  • Structure sustainable and ethical governance of AI tools across teams and departments.

Profil des bénéficiaires

Pour qui
  • Business or project managers working on data/AI implementation,
  • Managers from HR, Marketing, Communications, Legal, Innovation or IT departments,
  • Transformation or automation leads in charge of process improvement,
  • Product Owners, consultants, or “AI Champions” driving adoption within their teams.
Prérequis
  • Solid understanding of generative AI principles (LLM, prompting, use cases),
  • Regular experience using ChatGPT, Copilot, or similar AI tools in a professional context,
  • Familiarity with at least one workflow or automation tool (Notion, Zapier, Google/Microsoft Suite).

Contenu de la formation

Advanced Prompt Engineering (2h)
  • Modular structure: conditional segments, adaptive templates,
  • Role/format/style logic and output control techniques,
  • Model comparison and response optimization.
  • Practical activity : Design a prompt engine that dynamically generates a professional document (email, memo, HR note…) based on context.
Build a Generative Micro-Service (3h)
  • Chaining prompts with tools: e.g., ChatGPT → Google Sheets → Email,
  • Creating workflow automations using Make / Zapier,
  • Adding conditional logic and post-treatment layers.
  • Practical activity: Build a workflow-based AI assistant that generates a deliverable based on form inputs (HR report, meeting summary, content draft...).
Designing a Specialized Conversational AI Agent (2h)
  • Using memory/context features (e.g. GPT-4, Claude 3),
  • Designing structured expert personas with clear scopes and limits,
  • Managing consistency and fallbacks.
  • Practical activity: Create a legal or HR expert chatbot from a business corpus, and simulate a dialogue for accuracy testing.
Building AI Governance Structures (2h)
  • Human-in-the-loop, documentation, output auditing,
  • Input/output control: prompts, templates, post-processing,
  • Risk and responsibility distribution.
  • Practical activity: Build a governance grid for an AI use case: versioning, validation, access, risk levels, and human checkpoints.
Scaling and Industrializing Generative AI (2h)
  • Identifying scalable use cases,
  • Cost/benefit/risk modeling of AI assistants,
  • Moving from POC to organizational deployment.
  • Practical activity: Define a roadmap to industrialize an AI assistant in a real business context: milestones, risks, indicators, and teams.
Final Capstone Workshop (3h)
  • Design and simulate the deployment of a generative AI tool integrated in a workflow,
  • Evaluate performance, governance, and user engagement,
  • Pitch the result and receive peer feedback.

Équipe pédagogique

Professionnel expert technique et pédagogique.