DATA-642 Advanced Machine Learning (3)

This course explores state-of-the-art developments in machine learning and artificial intelligence (AI), emphasizing both theoretical foundations and practical applications. Topics include generative adversarial networks (GANs), graph neural and representation networks, and tensor/matrix factorization methods. Students study the mathematical principles behind these models and derive their corresponding optimization algorithms, gaining a deep understanding of how modern AI systems learn from complex and high-dimensional data. The course highlights cutting-edge applications of advanced machine learning across domains such as natural language processing, social and political analytics, and scientific discovery. Crosslist: DATA-442 . Prerequisite: STAT-627 .
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