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Pluralsight

Creating Synthetic Datasets with Generative AI

via Pluralsight

Overview

This course will teach you how to leverage Generative AI tools to produce quality synthetic datasets for testing, validation, training, and other data needs.

There is significant industry need for synthetic data to support testing, validation, demos, training scenarios and more. In this course, Creating Synthetic Datasets with Generative AI, you’ll gain the ability to effectively use generative AI to create professional-level synthetic datasets. First, you’ll explore assessing the true needs, parameters, and properties of a valid dataset. Next, you’ll discover how to leverage generative AI to produce these datasets, complete with bounds, data integrity, and even intentional errors common to real world datasets. Finally, you’ll see how prompt engineering best practices apply to iterate and refine your datasets. When you're finished with this course, you'll have the skills and knowledge needed to more confidently generate datasets with generative AI and be able to effectively leverage this skill in real-world settings.

Syllabus

  • Synthetic Datasets 15mins

Taught by

Russ Thomas

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