"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
Ce cours fait partie de Spécialisation Agentic AI Development & Security
Instructeur : LearningMate
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Ce que vous apprendrez
Learners will apply reinforcement learning to design and validate reward functions while analyzing ethical and societal implications of AI decisions.
Compétences que vous acquerrez
- Catégorie : Reinforcement Learning
- Catégorie : Risk Analysis
- Catégorie : Algorithms
- Catégorie : Regulatory Compliance
- Catégorie : Due Diligence
- Catégorie : Policy Analysis
- Catégorie : Policy Development
- Catégorie : Artificial Intelligence and Machine Learning (AI/ML)
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décembre 2025
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Il y a 2 modules dans ce cours
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.
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3 vidéos1 lecture1 devoir1 laboratoire non noté
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.
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3 vidéos1 lecture2 devoirs
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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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.
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¹ Certains travaux de ce cours sont notés par l'IA. Pour ces travaux, vos Données internes seront utilisées conformément à Notification de confidentialité de Coursera.