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Data science with social science data
January 12, 2017 @ 2:00 pm - 4:00 pm
Modern Languages Building (MLB), Room 2001B
This workshop covers the essential steps to data analysis in Python, using social science data as a case study. The workshop is divided into two parts. The first session includes an introduction to Python’s numpy and Pandas data analysis library. This session requires no previous experience with python. We will cover common steps involved in any data analysis: from loading the data to running a regression and interpreting outcomes.
The second session requires some background knowledge in python provided by the first session. The second session covers more advanced features, from various potential preprocessing steps to using Machine Learning Scikit-learn tools to analyze the data. As in the first session, we will be using an example from the social sciences.
The two sessions will be held in a computer lab and participants will be able to work either individually or in small groups on a few practice exercises.
- Class size
- U-M Affiliated Fee
- Not U-M Affiliated Fee
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