Synthetic Data: How To Use It and Generate It
Everything From The Programs To Use To The Types of Data You Can Create!
Description
Do you want to learn how to generate and use synthetic data for your business needs, such as testing, training, research, or analysis, without violating the privacy or confidentiality of the real data owners or subjects? Do you want to explore different techniques and tools for synthetic data generation, such as decision trees, deep learning techniques, and iterative proportional fitting? Do you want to discover some real-world use cases and examples of synthetic data in various domains, such as healthcare, finance, e-commerce, and social media? If yes, then this course is for you.
In this course, you will learn what synthetic data is, how to generate it, how to evaluate it, and how to use it effectively and efficiently in your business. You will also learn some best practices and tips for synthetic data generation and use, and some ethical and legal issues and challenges of synthetic data use. By the end of this course, you will be able to:
Understand the concept, importance, and benefits of synthetic data
Apply different techniques and tools for synthetic data generation, such as decision trees, deep learning techniques, and iterative proportional fitting
Measure and compare the quality and utility of synthetic data, using various metrics and criteria, such as statistical similarity, privacy preservation, and data utility
Follow some best practices and tips for synthetic data generation and use, such as working with clean data, assessing the similarity and utility of synthetic data, and outsourcing support if necessary
Explore some real-world use cases and examples of synthetic data in various domains, such as healthcare, finance, e-commerce, and social media
Discuss some ethical and legal issues and challenges of synthetic data use, such as data ownership, consent, and governance
This course is designed for anyone who is interested in learning about synthetic data, especially for business purposes. You do not need any prior knowledge or experience with synthetic data, but you should have some basic understanding of data analysis and statistics. You should also have access to a computer with an internet connection, and some software tools that we will use in this course, such as Gretel, Synthpop, and SDV.
What You Will Learn!
- Understand the concept, importance, and benefits of synthetic data
- Apply different techniques and tools for synthetic data generation, such as decision trees, deep learning techniques, and iterative proportional fitting
- Measure and compare the quality and utility of synthetic data, using various metrics and criteria, such as statistical similarity
- Explore some real-world use cases and examples of synthetic data in various domains, such as healthcare, finance, e-commerce, and social media
Who Should Attend!
- Anyone who is looking to learn more about synthetic data creation, especially for corporate use.