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There are 5 modules in this course
Welcome to "Responsible AI – Principles and Ethical Considerations"! Dive deep into the very essence of Responsible AI with us. Uncover the significance of key principles shaping technology's future. From ethical considerations to fairness, transparency, and accountability, we discuss these principles with real-world examples, putting them into the context of data science.
This course is designed for a diverse group of learners, including adult learners seeking to expand their knowledge, AI policy makers shaping the technological landscape, and leaders in the technology space specially navigating AI's strategic integration. This course also is helpful for AI Policy Makers, AI thought leaders, and anyone who are curious to harness AI's potential, rooted in distinct professional roles and aspirations.
Learn techniques to spot, tackle, and mitigate bias in AI algorithms, fostering fairness and inclusivity in AI systems. Discover the pivotal role of accountability in AI and its impact on ethical governance, privacy, and security throughout development and deployment. Striking the right balance between accuracy and explainability, you'll grasp the art of crafting an accountable and trustworthy AI system whose decisions can be easily interpreted.
By the course end, you'll not just understand the need for responsible AI but adeptly explain its principles and construct a solid framework for developing AI responsibly. This course doesn't just prepare you for a job; it empowers you with the knowledge to apply responsible AI principles ethically and develop AI systems responsibly.
To be successful in this course, understanding of the Basics of AI and Generative AI technologies and platforms, or knowledge of the nuances of social impact. Knowledge about the various legal and ethical frameworks would be an added advantage.
Join us in shaping the future responsibly!
In this module, you will learn about AI and the challenges it brings in different domains. You will be able to understand the need of Responsible AI and 6 principles of Responsible AI.
What's included
10 videos4 readings3 assignments1 plugin
Show info about module content
10 videos•Total 40 minutes
Course Introduction•4 minutes
What is AI?•5 minutes
Ethics in the Age of AI - The Challenges•4 minutes
AI & RAI Across Industries•5 minutes
RAI framework•3 minutes
AI- How can it be Fair•3 minutes
Data Principles - Data Privacy & Security•4 minutes
Importance of Transparency•5 minutes
Reliability, Stability & Accountability of AI•3 minutes
Inclusive and Socially responsible AI•5 minutes
4 readings•Total 75 minutes
Course Syllabus•30 minutes
The Need for Regulating AI•15 minutes
Use Cases across Industries and the need for RAI•15 minutes
Frameworks of RAI•15 minutes
3 assignments•Total 60 minutes
Fundamentals of responsible AI•15 minutes
Introduction to Responsible AI•15 minutes
Ensuring a Responsible Product•30 minutes
1 plugin•Total 15 minutes
YouTube Video: AI Is Dangerous, but Not for the Reasons You Think•15 minutes
Ensuring Fairness and Bias Mitigation
Module 2•2 hours to complete
Module details
In this module, you'll learn the concept of fairness within AI and gain insights into the different forms of biases that can infiltrate the machine learning pipeline. You will also learn about effective techniques for bias mitigation and measurement.
What's included
8 videos3 assignments1 discussion prompt
Show info about module content
8 videos•Total 33 minutes
Fairness in Data & Model•5 minutes
Bias in AI Learning•4 minutes
ML Pipeline - Where does bias creep in•4 minutes
Types of Biases in AI•5 minutes
Parity measures for Fair Decision Making•4 minutes
Techniques and strategies for Bias Measurement•6 minutes
Risks of Biased AI•3 minutes
Fireside Chat•2 minutes
3 assignments•Total 60 minutes
Bias and AI•15 minutes
Mitigating Bias in AI•15 minutes
Ensuring Fairness and Bias Mitigation•30 minutes
1 discussion prompt•Total 10 minutes
Biased AI and Their Consequences•10 minutes
Transparency and Explainability in AI
Module 3•1 hour to complete
Module details
In this module, you will explore the concept of transparency in AI, gaining a deep understanding of its importance. You'll also discover how transparency in data and models plays a crucial role in achieving explainability, ultimately leading to transparent and explainable business decisions.
What's included
5 videos2 assignments
Show info about module content
5 videos•Total 19 minutes
What is Explainability?•3 minutes
Explainability in AI Learning•5 minutes
Explainable Data•4 minutes
Explainable Models•3 minutes
Explainable Business•4 minutes
2 assignments•Total 45 minutes
Explainability in AI•15 minutes
Explainable Data and AI•30 minutes
Ensuring Accountability and Governance
Module 4•2 hours to complete
Module details
In this module, you'll learn the core concept of accountability in AI and its significance. Explore the concept of drift, including its various types, and delve into the diverse techniques for detecting drift in AI systems.
In this module, you'll learn the crucial need for data privacy in AI. Explore Privacy by Design, its foundational elements, and how it safeguards privacy in AI systems. Understand AI security and the concept of differential privacy for robust and private AI applications.
What's included
4 videos2 readings2 assignments
Show info about module content
4 videos•Total 16 minutes
Data Privacy and AI•4 minutes
AI Security•4 minutes
Privacy by Design - Foundational Elements•4 minutes
Differential Privacy•4 minutes
2 readings•Total 20 minutes
Considerations for Implementing Privacy by Design•10 minutes
Adversarial Attacks on AI•10 minutes
2 assignments•Total 45 minutes
Privacy, Security, and AI•15 minutes
Privacy and Security in AI•30 minutes
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Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.