The University of Texas at Austin 3 credits Data Science
Examine computing systems that automatically improve their performance with experience, including various approaches to inductive classification such as version space, decision tree, rule-based, neural network, Bayesian, and instance-based methods; as well as computational learning theory, explanation-based learning, and knowledge refinement. Only one of the following may be counted: Artificial Intelligence 391L, Computer Science 391L, Data Science 391L. The equivalent of three lecture hours a week for one semester. Pre/Corequisites: Graduate standing and Data Science 382.
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