Introduction to Python for Public Health Data Analysis | Brown School at Washington University in St. Louis
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Introduction to Python for Public Health Data Analysis

 

​Monday, June 26 - Friday, June 30, 2017

Registration deadline: June 2nd

8:30 - 11:30 a.m. each day

15 CEUs/CPH units

Paul Boal
Vice President of Delivery, Amitech Solutions

This course will introduce students to the fundamentals of the Python language, common Python modules for data manipulation and analysis, and Jupyter notebook environment. The course will begin with how to acquire data from publicly available sources and databases, cleansing and transformation of data, creation of descriptive statistics and graphics. The course will also introduce Python's natural language processing and machine learning modules for basic data classification and predictive modeling applications. Throughout the course, instruction and assignments will promote best practices for creating programs that can be shared and used for reproducible research.


Students taking this class should have experience doing data preparation or data analysis within the last 5 years. This could be demonstrated through previous work with statistical packages like R, SAS, SPSS, or Stata, or advanced data manipulation and analysis in Excel or Business Intelligence tools such as Tableau or Qlikview. Prior programming experience in Python is not required.Prerequisite:
Class size is limited to 15.
$650 General admission
$350 Non-profit/government employees (Additional Summer Institute classes)
$400 Non-profit/government employees (1st Summer Institute class)


This class will include both degree-seeking graduate students and practicing professionals. Individuals registering through Professional Development will not receive academic credit for the class.

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