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Advanced Gemini for Developers

Advanced Gemini for Developers

1h 10mAdvanced2025-05-22

Authors

Lynn Langit

Lynn Langit

Cloud Architect

Course details

In this course, learn to use Google Gemini applications patterns and scenarios for building LLM-based applications. These include patterns for prompt validation, effective RAG and LLM application building. Instructor Lynn Langit also includes comparisons using Model Garden with other foundation LLMs for your application scenarios.

Learning objectives
Use Google Gemini prompt validation, testing and management tools as you build your custom LLM-based applications.
Use the GCP Model Garden to explore, test and validate multiple foundational models.
Understand the next steps in mastering the efficient design, development, testing, hosting, and deployment of machine learning models for Google Gemini applications.

Skills covered

GeminiAI Productivity ToolsGenerative AIGoogleArtificial Intelligence for BusinessArtificial Intelligence (AI)Business Software and ToolsOne-Off

Concepts

0. Introduction

  • 01 - Creating enterprise GenAI apps with Google Gemini

1. Test Prompts

  • 02 - Test prompts with Prompt Tool
  • 03 - Configure Prompt Tool
  • 04 - Use Colab Enterprise with the Gemini API
  • 05 - Use CloudRun with the Gemini API

2. Manage Prompts

  • 06 - Use Prompt Management to write prompts
  • 07 - Use Prompt Management to compare prompts
  • 08 - Use Prompt Management to optimize prompts
  • 09 - Use Prompt Management to evaluate prompts

3. Use Model Garden

  • 10 - Test Gemini and Gemma models
  • 11 - Test open source models
  • 12 - Test Hugging Face
  • 13 - Test medical open source models

4. Build AI Applications

  • 14 - Explore AI applications and Vertex AI Search
  • 15 - Set up datastore for Vertex AI Search custom app
  • 16 - Build Vertex AI Search custom app
  • 17 - Explore Agent Garden capabilities

Conclusion

  • 18 - Next steps

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