GCP100GENAIPROMPT

Writing Effective Prompts for Generative AI Training

As generative AI becomes more common, the ability to interact with large language models is shifting from niche knowledge to a necessary skill across many different industries and roles. In this course, you will learn the fundamentals of prompting large language models and exploring further techniques for improving the output from large language models.

Google Cloud
✓ Official training Google CloudLevel Fundamentals⏱️ 0.5 day (3h)

What you will learn

  • Understand the basics of generative AI and how it compares to traditional AI.
  • Design effective prompts following general best practices.
  • Improve large language model outputs using easy-to-approach prompt engineering techniques.
  • Write effective prompts for interacting with multimodal models such as Gemini Vision Pro.

Prerequisites

  • There are no prerequisites for this course. The workshop aims to provide both introductory and advanced insights into Gen AI, making it suitable for individuals with varying levels of AI expertise.

Target audience

  • Customers

Training Program

5 modules to master the fundamentals

Objectives
  • Explain the capabilities of generative AI and list possible use cases.
Topics covered
  • →Definition of generative AI
  • →Capabilities of generative AI
  • →Tasks generative AI can help with
Activities

1x group discussion

Objectives
  • Identify the differences between keyword search and prompting, and list the benefits of prompting.
Topics covered
  • →Differences between keyword search and prompting
  • →Prompt examples
  • →The benefits of prompting
Activities

1x activity with Google Gemini

Objectives
  • Describe and apply prompt design best practices.
Topics covered
  • →The importance of prompt design
  • →General best practices
  • →Use prompt building blocks
  • →Provide examples
  • →Iterate through prompts
  • →Define follow-up prompts
  • →Chain-of-thought
  • →Prompt editor
Activities

6x demos

1x activity with Google Gemini

Objectives
  • Describe and apply approaches to improve the accuracy of generative AI responses.
Topics covered
  • →Hallucinations definition
  • →Use prompt instructions
  • →Grounding and citations
  • →Double-check responses
  • →Developer settings
Activities

3x demos

1x activity with Google Gemini

Topics covered
  • →Quiz questions
  • →Course summary
  • →Q&A
Activities

1x quiz

Related Trainings

Upcoming sessions

October 21, 2026
Distanciel • Français
Register

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.
  • Group Discussion — Open exchange among peers and the instructor on a specific topic.
  • 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.

790€ excl. VAT

per learner