96-777 Data Analytics

6 units, Carnegie Mellon University

This course on data analytics is designed to give students a thorough grounding in the methods, theory, mathematics and algorithms needed to apply analysis methods from machine learning and statistics. The topics of the course draw from machine learning, classical statistics, Bayesian statistics, probability, data mining, information theory, and other areas. This course is project-oriented and is intended to give students abundant hands-on experience with different analysis techniques. Some prior knowledge of probability, statistics, and programming is assumed. However, knowledge of a particular programming language is not required.

Prerequisites: none listed

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