Responsible AI - Principles and Ethical Considerations
Master ethical AI principles, fairness, transparency, and accountability in AI systems. Essential for technology leaders and policymakers.
Master ethical AI principles, fairness, transparency, and accountability in AI systems. Essential for technology leaders and policymakers.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Leadership Strategies for AI and Generative AI Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Understand and apply responsible AI principles in technology development
Identify and mitigate bias in AI algorithms and data systems
Implement transparency and explainability in AI decision-making
Establish accountability and governance frameworks for AI systems
Apply privacy and security measures in AI development
Skills you'll gain
This course includes:
2 Hours PreRecorded video
12 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course explores the fundamental principles and ethical considerations of Responsible AI. Students learn about key concepts including fairness, transparency, accountability, and bias mitigation in AI systems. The curriculum covers practical techniques for identifying and addressing algorithmic bias, ensuring AI explainability, implementing privacy-by-design principles, and establishing effective AI governance frameworks. Through real-world examples and case studies, learners develop skills in building ethical and responsible AI systems that balance accuracy with interpretability.
Introduction to Responsible AI
Module 1 · 3 Hours to complete
Ensuring Fairness and Bias Mitigation
Module 2 · 1 Hours to complete
Transparency and Explainability in AI
Module 3 · 1 Hours to complete
Ensuring Accountability and Governance
Module 4 · 1 Hours to complete
Privacy and Security in AI
Module 5 · 1 Hours to complete
Fee Structure
Instructors
Leading the Future of AI Education with Comprehensive Course Portfolio
Fractal Analytics has established itself as a premier provider of cutting-edge technology education through its extensive course offerings on Coursera, spanning artificial intelligence, data science, and business strategy. The curriculum encompasses sixteen specialized courses, including foundational programs like "Python for Data Science" and "Structured Approach to Problem Solving," alongside cutting-edge offerings in Generative AI with courses such as "GenAI for Everyone," "Generative AI Essentials," and "Coding with Generative AI." The platform demonstrates its commitment to responsible technology implementation through courses like "Responsible AI - Principles and Ethical Considerations" and "Responsible AI in the Generative AI Era," while also addressing human aspects of technology through "Behavior Architecture - Understanding Human Behavior" and "Human Decision Making and its Biases." Advanced technical courses include "Introduction to Vertex AI" and "Quantum Computing For Everyone," complemented by practical business applications through "Data Storytelling," "Generative AI for Consultants," and "Successful AI Strategies: A CEO's Perspective." This comprehensive portfolio reflects Fractal Analytics' dedication to providing well-rounded education in emerging technologies while emphasizing ethical considerations and practical applications.
Pioneering Responsible AI Leadership and Innovation
Sray Agarwal has established himself as a distinguished leader in Data and Artificial Intelligence, particularly championing Responsible AI (RAI) frameworks across international platforms. His multifaceted role at Fractal Analytics encompasses providing pre-sales support globally, mentoring teams in emerging technologies, and serving as a Coursera instructor for Responsible AI. His credentials include authoring a book on Responsible AI, earning a Microsoft MVP award, and serving as an expert advisor to the United Nations. His educational background combines a PGP in Business Analytics from ISB, a Master's in Economics from Mahatma Gandhi University, and a Global Management Programme from Darden Business School. As a Principal Consultant with over 13 years of industry experience, he has pioneered RAI frameworks for major banks in the UK and US, while regularly contributing to international forums including Davos 2024. His expertise spans credit risk modeling, financial crime detection, and graph-based crime modeling, utilizing technologies like Python, R, Spark, AWS, and Azure. Through his practical, hands-on teaching approach, he focuses on equipping learners with skills for effective digital transformation while ensuring AI projects prioritize human, societal, and environmental values
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