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
4.3/5 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
Welcome
Chapter 1. The State of Ethics, Trust & Responsibility with AI and Data Science
Chapter 2. What do we mean by Artificial Intelligence and Data Science and Why It Matters
Chapter 3. Strategies (& Challenges) of Putting Ethics & Responsibility into Practice
Final Exam (Verified track only)

Prerequisites
Reviews
Dec 2022
I feel that this course is suitable for any student, regardless of their IT background.
Dec 2022
It was thought-provoking. I learned a lot, and I really enjoyed this course.
Oct 2022
The content provided was sufficient. I liked how it started from general AI, and then went to deeper parts, it made it easier to learn.
Oct 2022
I liked that this course covered the topic in a conversational way, it was easy to follow, and structured to be bite-sized and not overwhelming.
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.