"Design Ethical AI Rewards and Policies" is an engaging course for professionals, data scientists, AI practitioners, and decision-makers seeking to implement responsible AI practices in their organizations. In an era where AI systems significantly impact business operations, understanding how to balance performance metrics with ethical considerations is crucial. This course provides a comprehensive foundation in the principles of reinforcement learning, focusing on creating effective reward functions that align with business goals while ensuring compliance with ethical standards. Through hands-on labs, interactive dialogues, and real-world case studies, you will learn to identify and mitigate biases in AI policies, including adherence to global regulatory frameworks like GDPR. By integrating theory with practical application, this program equips you with the skills to lead initiatives that prioritize fairness and accountability in AI development. Whether your goal is to enhance customer interactions or ensure ethical governance, this course lays the groundwork for building trustworthy AI systems that deliver value without compromising integrity.
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Design Ethical AI Rewards and Policies
This course is part of Agentic AI Development & Security Specialization
Instructor: LearningMate
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Recommended experience
What you'll learn
Learners will apply reinforcement learning to design and validate reward functions while analyzing ethical and societal implications of AI decisions.
Skills you'll gain
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December 2025
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There are 2 modules in this course
This module provides an in-depth understanding of the principles of reinforcement learning to design and tune effective AI agent incentives. You will learn how to create reward functions that balance competing business goals, such as maximizing customer satisfaction while minimizing operational costs. Through hands-on off-platform practice, you will implement and validate reward weighting schemes for a customer-support chatbot, directly applying the skills needed to align agent behavior with desired outcomes.
What's included
3 videos1 reading1 assignment1 ungraded lab
This module focuses on the critical skills of risk analysis and due diligence for AI systems. You will learn to analyze an agent's decision policy for ethical, legal, and societal implications, with a focus on identifying and mitigating bias. Using standard documentation practices, you will conduct a bias audit, cite relevant legal considerations like the General Data Protection Regulation (GDPR), and document your findings and mitigation steps in a formal accountability matrix.
What's included
3 videos1 reading2 assignments
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