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.
What you will learn
- Define generative AI and distinguish between generative AI and other types of AI.
- Define the potential personas affected by generative AI and how they can leverage this new technology.
- Gain insights into real-world generative AI use cases across industries, such as Retail, Automotive, Software Development, and Financial Services.
- Identify and prioritize possible applications in your organization.
- Understand the pillars of Responsible AI and how it relates to generative AI.
- Explain the importance and value of prompt design.
- Design effective prompts following general best practices.
Target audience
- Business users, Business leaders, Decision makers, Customers
Training Program
7 modules to master the fundamentals
Objectives
- Define generative AI as a subset of AI.
- Discuss AI's potential impact on organizations.
- Provide examples of generative AI applications.
Topics covered
- →Generative AI vs. AI/ML
- →Gen AI Use Cases
- →Business Applications of Gen AI
Objectives
- Define the different personas in your organization for generative AI.
- Explore different services for the different personas in your organization.
Topics covered
- →Personas and products
- →Business audience: Workspace
- →Consumer AI products vs. Enterprise AI
- →General Audience: Vertex AI Studio
- →AI Practitioners: Model Garden
- →Power Users: Vertex AI Agent Builder
Objectives
- Understand common business challenges across different industries.
- Explore use cases for generative AI across different industries.
Topics covered
- →Common business challenges
- →Use cases across different industries
Objectives
- Identify Gen AI use cases for your organization.
- Evaluate and prioritize generative AI use cases.
Topics covered
- →Use case identification
- →Scoping considerations
- →Use case prioritization and evaluation
Activities
Activity: Brainstorm Gen AI use cases for your organization
Objectives
- Learn how Google approaches Responsible AI.
- Define the pillars of Responsible AI at Google.
- Understand the relationship between data privacy and generative AI.
Topics covered
- →Data Privacy at Google
- →AI and responsibility
- →Google's AI principles
- →Responsible AI best practices
Objectives
- Understand the importance of prompt design for generative AI.
- Write effective prompts for interacting with LLMs.
Topics covered
- →What is prompt design and why is it important?
- →Prompt content types
- →Prompt design strategies
- →Iterating prompts for improvement
Activities
Lab: Introduction to Prompt Design
Objectives
- Use prompt design strategies to improve output from LLMs.
Topics covered
- →Prompt design vs. prompt engineering
- →Zero-shot and few-shot prompting
- →Chain of thought prompting
- →Overview of additional techniques
Activities
Lab: Improving Your Prompts
Optional Lab: Writing Prompts for Gemini Pro Vision
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.
- 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).
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.
Train multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote