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Explores how AI/ML is shaping the future workplace, focusing on enterprise systems and processes, and discusses the current state of AI/ML adoption in enterprises.
Introduces Hidden Markov Models, explaining the basic problems and algorithms like Forward-Backward, Viterbi, and Baum-Welch, with a focus on Expectation-Maximization.
Explores the challenges and distinctions between human and artificial autonomy, touching on ethical implications and the conditions required for true autonomy.
Explores Kantian ethics, virtues, and the common good in engineering decision-making, emphasizing the ethical implications of individual actions on collective well-being.
Explores legal obligations and ethical considerations in data processing and AI, covering consumer credit, data protection, and automated decision-making.
