Introduction to Developer Efficiency on Google Cloud
- Código del Curso GO8340
- Duración 1 Día
Otros Métodos de Impartición
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Método de Impartición
Este curso está disponible en los siguientes formatos:
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Cerrado
Cerrado
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Clase de calendario
Aprendizaje tradicional en el aula
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Aprendizaje Virtual
Aprendizaje virtual
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Temario
Parte superiorGenerative 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.
Updated Sept. 2026
Company Events
These events can be delivered exclusively for your company at our locations or yours, specifically for your delegates and your needs. The Company Events can be tailored or standard course deliveries.
Calendario
Parte superiorDirigido a
Parte superior- Developers
Objetivos del Curso
Parte superiorAfter this course participants should be able to:
- 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).
- 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.
- 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.
- Understand the role of Vertex AI Model Garden.
- Explore models available in Vertex AI Model Garden.
Contenido
Parte superior1- Developer Efficiency on Google Cloud
- Developer workflows and efficiency challenges
- Developer efficiency on Google Cloud
- AI-powered developer tools on Google Cloud
- Developer workflows with LLMs
2- Using Gemini Throughout the Development Lifecycle
- 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
- Lab: Using Gemini Throughout the Software Development Lifecycle
3- Prompt Design for Gemini
- Why prompt design is important
- General prompt design tips
- Prompt design for Gemini
- Lab: Prompt Design for Gemini Code Assist
4- Leveraging Codey in Developer Workflows
- 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
- Lab: Leveraging Codey in Your Applications
5- Discovering Model APIs Using Vertex AI Model Garden
- Vertex AI Model Garden
- Model types and solutions
- Model Registry and model deployment
- Fine-tuning models
- Lab: Exploring Vertex AI Model Ga
Pre-requisitos
Parte superior- Google Cloud Fundamentals: Core Infrastructure or equivalent Google Cloud experience.
Certificación de Prueba
Parte superiorNone
