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Ethical AI

Course

In this course, students will learn how to approach and apply ethical AI. Coursework will enable practitioners to design and build models with enhanced fairness and limited bias to avoid unforeseen consequences and connect ethical AI concepts to critical issues in privacy, governance, transparency, and security. They’ll begin with acquiring ethical AI literacy skills that will enable them to engage in more meaningful discussions across AI disciplines and learn how to apply ethical AI principles to their organization. Students will then learn how to implement technical measures toward bias, fairness, and explainability to help ensure an ethical future for all.

In this course, students will learn how to approach and apply ethical AI. Coursework will enable practitioners to design and build models with enhanced fairness and limited bias to avoid unforeseen consequences and connect ethical AI concepts to critical issues in privacy, governance, transparency, and security. They’ll begin with acquiring ethical AI literacy skills that will enable them to engage in more meaningful discussions across AI disciplines and learn how to apply ethical AI principles to their organization. Students will then learn how to implement technical measures toward bias, fairness, and explainability to help ensure an ethical future for all.

Intermediate

4 weeks

Real-world Projects

Completion Certificate

Last Updated December 15, 2022

Skills you'll learn:
AI Governance • Model bias analysis • Ethical AI • Explainable AI
Prerequisites:
AI fluency • Python data analysis libraries • Machine learning model implementation

Course Lessons

Lesson 1

Introduction to Ethical AI

Learn the fundamentals of AI Ethics, including the definitions, history, context, and stakeholders involved with this domain!

Lesson 2

AI Ethics for Organizations

Learn how to articulate and apply ethical AI for organizations and businesses, including how bias applies to organizations, ethical AI principles and programs, and guardrails!

Lesson 3

Identifying Bias Towards Fairness

Learn how to identify the different types of AI biases and harms, and apply harm quantification metrics for evaluating fairness!

Lesson 4

Mitigating Bias Towards Fairness

Learn how to mitigate bias, including comparisons between strategies and metrics, and applying techniques toward enhancing fairness!

Lesson 5

Transparency, Trust, and Explainability

Learn how to articulate context around AI regulations, data governance, and auditing! Along the way, you will also learn how to apply techniques for transparency and explainability.

Lesson 6 • Project

AI Ethics for Personalized Budget Prediction

Test your skills for identifying the ethical impact of a use case! You'll perform quantitative analyses, mitigate bias, and create a model card to document the ethical impact and your findings!

Taught By The Best

Photo of Ria Cheruvu

Ria Cheruvu

Intel NEX AI Ethics Lead Architect

Ria is Intel NEX AI Ethics Lead Architect, leading trustworthy AI. She is an emerging industry speaker and has a master's in data science from Harvard University. Ria previously served as a Teaching Fellow for Harvard's 2021 Data Science graduate curriculum and Lead Instructor for Eduonix's ML Deployment course.

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Demonstrate proficiency with practical projects

Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

  • Gain proven experience

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Top-tier services to ensure learner success

Reviewers provide timely and constructive feedback on your project submissions, highlighting areas of improvement and offering practical tips to enhance your work.

  • Get help from subject matter experts

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  • Gain valuable insights and improve your skills