Data Literacy Essentials: Ethics in Augmented Analytics
This course will teach you to ensure ethical implementation of augmented analytics in your organization.
What you'll learn
The ability to manage and understand data has been an increasingly important skill that is vital to any organization in the present times. However, data nowadays has been increasingly becoming complex, difficult to understand, and subject to risk and bias. In this course, Data Literacy Essentials: Ethics in Augmented Analytics, you’ll learn how to ensure ethical implementation of augmented analytics in your organization.
First, you’ll explore what ethics in augmented analytics is, its relevance, and the key areas to address for a proactive approach in ensuring ethical implementation. Next, you’ll discover data bias, its different types, and corresponding mitigation strategies. Finally, you’ll learn how to understand the concept of Explainable AI, its relevance, considerations to drive desirable outcomes with it, as well as the primary concerns that drive the need for Explainable AI. When you’re finished with this course, you’ll have the skills and knowledge that will help you ensure ethical implementation of augmented analytics in your organization.
Table of contents
- Augmented Analytics Concept: Machine Learning 6m
- Augmented Analytics Concept: Artificial Intelligence and Augmented Analytics 5m
- Ethics in Augmented Analytics 5m
- Relevance of Ethics in Augmented Analytics 3m
- Key Areas to Address to Ensure Ethical AI 4m
- Use Case: Identifying Key Areas to Ensure Ethical AI and Augmented Analytics 6m