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This course is an introduction to the basic concepts and principles of data analytics using the Python programming language. The first part of the course covers major Python language topics including procedures and functions, iteration, recursion, arrays and matrices, strings, operational model of procedure and function calls, algorithms, exceptions, object-oriented programming, and file input/output. The coverage of Python language features are aimed mainly at the data analytics studies of this course. The second part of the course emphasizes applying Python and its rich functional libraries and special software packages to data munging, analysis, mining, and visualization, and machine learning techniques including statistical analysis, parameter estimation, regression, classification, predictive modeling construction, etc.

Prerequisite(s)/Corequisite(s): (CSCI 1620 with grade of C or better) AND (CIST 2500 or equivalent statistics course with grade of C- or better). Not open to non-degree graduate students.