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Pluralsight

Google Gemini Security and Cost Optimization

via Pluralsight

Overview

In today's digital world, knowing how our data is handled is quite essential. This course will teach you about the data privacy, retention and training policy for Google Gemini.

In today's age of artificial intelligence, understanding how our data is processed, stored, and used is of paramount importance. In this course, you’ll learn how to use Google Gemini effectively while ensuring data privacy and boosting performance. First, you'll start by understanding data privacy rules and how Google Gemini handles, processes, and protects the user data. Next, you'll explore data retention, and training policies, and how regulations like CCPA and GDPR affect your interactions with Gemini. Then, you'll gain insights into evaluating performance factors, including the impact of model size and complexity on inference time and resource utilization. Finally, you'll discover techniques for optimizing API requests and responses to enhance overall system efficiency. When you’re finished with this course, you’ll have the skills and knowledge needed to effectively navigate data privacy concerns and optimize performance within the realm of Google Gemini, empowering you to confidently leverage its capabilities for your organization's success.

Syllabus

  • Data Privacy in Google Gemini 12mins
  • Key Drivers for Google Gemini’s Performance 14mins

Taught by

Avdhesh Gaur

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