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.
Author Name: Avdhesh Gaur
Author Description:
Avdhesh Gaur is a Senior Data Scientist, an instructor, an author, a storyteller and consultant as well when it comes to bringing insights out of data and presenting the story behind. His career spans more than 10 years with a focus on taking down various business requirements by building Data-driven BI models using Tableau, SQL, Hive, and numerous Statistical data analysis Techniques. Avdhesh Gaur got one of his submissions to Tableau accepted on 7th January 2019. On average, only 1 out of ev… more

Table of Contents

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