🏆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

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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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