Course Overview
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.
Who should attend
Application developers and others who wish to understand how generative AI on Google Cloud can make development more efficient
Prerequisites
Google Cloud Fundamentals: Core Infrastructure (GCF-CI) or equivalent Google Cloud experience.
Course Objectives
- 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.
Follow On Courses
Outline: Introduction to Developer Efficiency with Gemini on Google Cloud (IDEGC)
Module 1 - Developer Efficiency on Google Cloud
Topics:
- Developer workflows and efficiency challenges
- Developer efficiency on Google Cloud
- AI-powered developer tools on Google Cloud
- Developer workflows with LLMs
Objectives:
- 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).
Module 2 - Using Gemini Throughout the Development Lifecycle
Topics:
- Introduction to Gemini for Google Cloud
- Cloud Code and Gemini Code Assist
- Generating and completing code by using Gemini Code Assist
- Understanding logs using Gemini
Objectives:
- Use Gemini Code in Cloud Code to more efficiently write code for your applications.
- Use Gemini in Google Cloud to quickly summarize your application logs.
Activities:
- Lab: Using Gemini Throughout the Software Development Lifecycle
Module 3 -Prompt Design for Gemini
Topics:
- Why prompt design is important
- General prompt design tips
- Prompt design for Duet AI
Objectives:
- Explain the fundamentals of prompt design when using Gemini Code Assist.
Activities:
- Lab: Prompt Design for Gemini Code Assist
Module 4 - Leveraging Codey in Developer Workflows
Topics:
- Vertex AI Gemini and PaLM API
- Code generation and completion with Codey
- Vertex AI Studio
- Using the Codey API in your code
- Fine-tuning Codey for specific use cases
Objectives:
- Use the Vertex AI Gemini API, PaLM API and Codey for code generation
- Integrate Codey into applications by using the API
- Fine-tune Codey for specific use cases
Activities:
- Lab: Leveraging Codey in Your Applications
Module 5 - Discovering Model APIs using Vertex AI Model Garden
Topics:
- Vertex AI Model Garden
- Models types and solutions
- Model Registry and model deployment
- Fine-tuning models
Objectives:
- Understand the role of Vertex AI Model Garden.
- Explore models available in Vertex AI Model Garden.
Activities:
- Lab: Exploring Vertex AI Model Garden