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University of Michigan School of Information


370 - Data Exploration

Data Exploration --- The exploratory data analysis and visualization course aims to help students get started with their own data acquisition and exploratory analysis. Exploratory data analysis is crucial to evaluating and designing solutions and applications, as well as understanding information needs and use. Students in this course will learn basic concepts of information visualization and techniques of exploratory data analysis, using scripting, text parsing, structured query language, regular expressions, graphing, and clustering methods to explore data. Students will be able to make sense of and see patterns in otherwise intractable quantities of data. In this course students will be able to work with the Pandas, seaborn, and scikit-learn packages of Python.
Credit Hours 4


  • SI 330 and (STATS 250 or waiver); (C- or better)