Registration deadline: May 31st
This course will be conducted via a virtual Zoom meeting format and Canvas. Access to a computer/laptop with internet access is required. Please contact Professional Development with any questions.
15 CEUs/CPH units - (7.5 live, 7.5 self-paced)
Dominique Lockett, MA
Adjunct Faculty, Brown School 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, and the 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.
Note: 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.
The course will consist of daily live Zoom class meetings from 2:00 - 3:30 p.m. (Central Time), and additional course material in Canvas.
Class size is limited to 25.
$650 General admission
$450 Non-profit/government employees (1st Summer Institute class)$400 Non-profit/government employees (Additional Summer Institute classes)
This
class will include both degree-seeking graduate students and practicing
professionals. Individuals registering through Professional Development
will receive continuing education units - but not academic credit - for
the class.
About the Instructor:
Dominique Lockett is a current PhD student in political
science at Washington University. Her major research interests are political
methodology, political behavior, and identity in American politics. She
contributes to teaching Political Data, which trains students to effectively
manage, analyze and visualize data. Dominique holds a Master’s degree in
political science from St. Louis University.
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