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This course on data ethics aims to teach learners about the importance of ethical considerations in the realm of algorithms, machine learning, artificial intelligence, and data analytics. The course covers topics such as ethical auditing of algorithms, ensuring fairness, accountability, transparency, interpretability, and group privacy in complex algorithmic systems. It also addresses the prevention and identification of discriminatory outcomes in decisions made by AI systems. The intended audience for this course includes individuals interested in understanding the ethical implications of emerging information technologies, particularly in the context of data science and AI. The teaching method involves exploring case studies, discussing ethical challenges, and examining general approaches to ethical decision-making in algorithmic systems.
