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.
Author Name: Wilvie Anora
Author Description:
She is the Co-founder as well as Strategy Lead of AtoANI (sustainable agriculture) and AtoANI BioPack (biodegradable packaging). She is passionate about Social Innovation and using it to contribute to the UN Sustainable Development Goals. With a Chemical Engineering and MBA Degree, her corporate experience in multinational companies involves working on various topics in the areas of Strategy, Digitalization, Innovation, Finance, Material Management, Quality Assurance, Program and Project Managem… more

Table of Contents

• Course Overview
  1min
• Ethics in Augmented Analytics Overview
  28mins
• Understanding Data Bias
  27mins
• Understanding the Concept of Explainable AI
  24mins