🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
🏆SFEIR is the Google Cloud EMEA Training Partner of the Year 2025🤝New partnership: Official GitLab Training🤖New training: AI-Augmented Developer
GCP100AILEADER

Generative AI Leader

In this course, you will take a journey from a broad overview of gen AI to understanding how to leverage gen AI and Google Cloud for organizational transformation.

Google Cloud
✓ Official training Google CloudLevel Fundamentals⏱️ 2 days (14h)

What you will learn

  • Describe how generative AI transforms organizations across business functions and industries.
  • Define core gen AI concepts (artificial intelligence, gen AI, machine learning, etc.).
  • Identify the core layers of the gen AI landscape (applications, agents, platforms, models, and infrastructure).
  • Explain how you can combine the components of generative AI agents to build powerful solutions.
  • Identify Google Cloud products and solutions that support the implementation and scaling of generative AI initiatives.

Prerequisites

  • None

Target audience

  • Business professionals of all levels and job roles who want to contribute to their company's gen AI transformation

Training Program

5 modules to master the fundamentals

Objectives
  • Discover how generative AI transforms organizations across business functions and industries.
  • Explore how generative AI uses foundation models and prompt engineering to create value.
  • Identify Google Cloud's unique strengths in the field of generative AI.
  • Explain the Google-Cloud-recommended steps to successfully implement a transformational gen AI solution.
Topics covered
  • →Introduction to gen AI for businesses
  • →Introduction to gen AI foundations
  • →Gen AI strategy
Activities

Discussion: What is your why?

Discussion: Feeling inspired

Try it: Hands-on with the Gemini app

Discussion: Benefits of Google Cloud when building AI solutions

Try it: Prioritization exercise

Activity: Augmentation or automation?

Objectives
  • Define core generative AI concepts.
  • Explain how data types are used in generative AI for business solutions, innovation, and competitive edge.
  • Explain the role of foundation models in generative AI.
  • Describe the Google-Cloud-recommended strategies for handling LLM limitations.
  • Describe the challenges and key factors involved in responsibly and securely developing and deploying AI.
Topics covered
  • →Core gen AI concepts
  • →Foundation models
  • →Responsible AI
Activities

Activity: Supervised, unsupervised, or reinforcement learning?

Discussion: Model matchmaker

Discussion: Organizational roadblocks to responsible AI

Objectives
  • Describe the layers of the gen AI landscape.
  • Determine strategic entry points within the gen AI landscape to address specific business needs and drive innovation.
  • Describe the components of the Google Cloud gen AI portfolio.
  • Explain how Google Cloud's AI-optimized resources support gen AI development.
  • Describe the business factors to consider when deciding what to use for specific applications.
Topics covered
  • →The gen AI landscape
  • →Gen AI agents and applications
  • →Gen AI platform, model, and infrastructure
  • →Gen AI project resources and management
Activities

Discussion: Conversational and workflow agents

Activity: The writing assistant

Activity: Edge or cloud?

Activity: Best solution

Objectives
  • Explain prompt engineering techniques and how they drive better results.
  • Develop automated workflows by using generative AI prompt templates and tools.
  • Describe the core functionality and business value of using Gemini for Google Workspace.
  • Describe the core functionality and business value of using Gemini for Google Cloud.
Topics covered
  • →Prompting techniques
  • →Gen AI for productivity
  • →Gemini for Google Cloud
Activities

Discussion: Customer service

Try it: Step into the role

Activity: Pick-a-product

Discussion: Gemini for Google Cloud in your organization

Objectives
  • Define the components of generative AI agents and how they work together.
  • Explain how you can combine the components of generative AI agents to build powerful solutions.
  • Describe how you can use Google Cloud's gen AI products to create generative AI agents and solutions.
  • Explain how to effectively lead and manage organizational transformation with gen AI.
Topics covered
  • →Today's agents
  • →Building agents
  • →Enhancing the customer experience with agents
Activities

Activity: The better prompt technique

Activity: Agent tooling example – Meeting location planner APIs

Activity: Pick-a-product

Related Trainings

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Empower Decision Makers with Generative AI

This course is designed for business users, business leaders, and decision makers who want to understand the transformative potential of generative AI and its impact on their organizations. You'll gain a comprehensive understanding of this technology, learn how it can be leveraged to drive innovation and efficiency, and explore the range of generative AI services available on Google Cloud. By the end of this course, you'll be equipped to make informed decisions about implementing AI solutions.

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Upcoming sessions

June 3, 2026
Distanciel • Français
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August 3, 2026
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October 1, 2026
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December 3, 2026
Distanciel • Français
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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

Teaching Methods Used
  • Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
  • Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
  • Guided Labs — Guided practical exercises on software, hardware, or technical environments.
  • Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
Evaluation and Monitoring System

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.

1,580€ excl. VAT

per learner

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