Training > AI/Machine Learning > Ethics in AI and Data Science (LFS112x)
Training Course

Ethics in AI and Data Science (LFS112x)

Learn how to build and incorporate ethical principles and frameworks in your AI and Data Science technology and business initiatives to add transparency, build trust, drive adoption, and lead with responsibility.

Course Rating
4.2/5 Stars
Who Is It For

The course is designed for business, government and technology leaders and data scientists who are responsible for building and adopting AI tools.
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What You’ll Learn

In this course you will learn about business drivers for AI, the ethical challenges and impacts of AI and Data Science, the business and societal dynamics at work in an AI world, the key principles for building responsible AI, and more. This course introduces some of the principles and frameworks that puts ethics and responsibility into practice in the data analytics profession. And offers practical approaches to technical, business and leadership dilemmas and challenges posed by work in AI and Data Science.
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What It Prepares You For

You will walk away from this course with an understanding of how to add transparency, develop standards and share best practices to build trust and drive AI adoption.
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Course Outline
Chapter 1. What’s at Stake? The Need for Ethics, Trust & Responsibility
Chapter 2. What do we mean by Artificial Intelligence?
Chapter 3. The Complex World of Data
Chapter 4. The Challenges & Strategies for Putting Ethics into Practice
Final Exam (Verified track only)

Aug 2022
Very comprehensive overview of the importance of committing to a conscious, pro-active focus on equanimity in the AI systems. We develop and maintain a clear view of the endgame goal of bringing benefit to many, rather than an elite few.
Jun 2022
I liked the vast amount and variety of content, and the inclusion of in-depth explanations.
Jun 2022
The effort put into the gathering of data, and designing it in a presentable manner, was the most amiable part. I also liked the fact that most of the content was short and coverable.
May 2022
This is really something for us in the university to talk about. The pandemic has induced tremendous online activity, and with it, online data. We need to start talking about responsibility, accountability, transparency, explainability, privacy...and delight. What will delight our stakeholders?