GCP100DEVEFF

Introduction to Developer Efficiency with Gemini on Google Cloud

Generative AI is now at the center of transforming how software is designed, built, run, and managed. For developers, generative AI is a powerful tool for making coding more efficient and using APIs, such as the Gemini and PaLM APIs, within their applications. In this course, you are introduced to how generative AI can be used to make developers more efficient at writing code and implementing new features into applications. You will also explore available models in Vertex AI Model Garden.

✓ Formation officielle Google CloudNiveau Fundamentals⏱️ 1 jour (7h)

Ce que vous allez apprendre

Understand the efficiency challenges in a developer workflow and how generative AI can make developers more efficient.
Use Gemini Code Assist to more efficiently write code for your applications.
Use Gemini in Google Cloud to quickly summarize your application logs.
Explain the fundamentals of prompt design when using Gemini Code Assist.
Integrate the Gemini and PaLM APIs in your applications to use generative AI.
Explore available models in Vertex AI Model Garden.

Prérequis

Google Cloud Fundamentals: Core Infrastructure or equivalent Google Cloud experience.

Public cible

Developers

Programme de la Formation

5 modules pour maîtriser les fondamentaux

Objectifs

Describe efficiency challenges that developers face.
Understand how AI-powered tools on Google Cloud can improve developer efficiency.
Describe developer workflows when using large language models (LLMs).

Sujets abordés

→Developer workflows and efficiency challenges
→Developer efficiency on Google Cloud
→AI-powered developer tools on Google Cloud
→Developer workflows with LLMs

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.