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Starts 5 June 2025 19:26

Ends 5 June 2025

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Prompt Engineering for Developers with Google Gemini

Master prompt engineering for Google Gemini models, learning to craft effective prompts, use the API, optimize settings, and design prompts for specific use cases to achieve optimal results.
via Pluralsight

659 Courses


13 minutes

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Overview

Generating useful and reliable outputs from large language models depends heavily on how you prompt them. In this course, Prompt Engineering for Google Gemini, you’ll learn to use the Gemini large language models efficiently through prompt engineering.

First, you’ll explore the basics of prompt engineering. Next, you’ll discover how to call the Gemini models programmatically through their API, as well as the different settings that can be used to drive the most out of these models.

Finally, you’ll learn how to craft prompts for specific use cases. When you’re finished with this course, you’ll have the skills and knowledge needed to get the most optimal results from the Gemini language models.

Syllabus

  • Introduction to Prompt Engineering
  • Overview of large language models and their capabilities
    Importance of prompts in generating outputs
    Fundamentals of crafting effective prompts
  • Understanding Google Gemini
  • Introduction to Google Gemini large language models
    Key features and specifications of Gemini models
  • Accessing Gemini Models Programmatically
  • Setting up the environment
    Introduction to Gemini API
    Authentication and API key management
    Making API calls to interact with Gemini models
    Handling responses and integrating into applications
  • Advanced Prompt Engineering Techniques
  • Exploring prompt formats and structures
    Using context and instructions to refine outputs
    Experimenting with temperature, max tokens, and other settings
    Techniques for debugging and optimizing prompts
  • Crafting Prompts for Specific Applications
  • Common use cases and application scenarios
    Designing prompts for text generation tasks
    Creating prompts for code generation and data analysis
    Customizing prompts for interactive applications
  • Best Practices and Ethical Considerations
  • Ensuring output reliability and accuracy
    Maintaining ethical standards in prompt crafting
    Addressing biases and content moderation
  • Conclusion and Next Steps
  • Recap of key learning outcomes
    Resources for further learning and practice
    Course wrap-up and feedback session

Taught by

Laurentiu Raducu


Subjects

Computer Science