The College of Behavioral and Social Sciences wants to offer you the opportunity to gain important data science skills and earn elective credit. By building your resume with these valuable skills, you will become more marketable to employers.

These courses are open to all BSOS majors.


BSOS233: Data Science for the Social Sciences (Fall 2019) - 3 credits

Interested in understanding how Python can be used for data analysis? In BSOS233, students will be given an introduction to modern methods of data analysis for social scientists.  This course emphasizes teaching students who have no previous coding experience how to analyze data and extract meaning in a social science context.  Students will gain critical programming skills and learn inferential thinking through examples and projects with real-world relevance. Instructors: Brian Kim, Yan Li. Course meets Tuesdays/Thursdays 12:30-1:45pm in ASY 3207.

Open to all BSOS  majors or by permission of instructor. Register on Testudo


BSOS330: Programming for the Social Sciences: Statistical Computing Using R (Fall 2019) - 1 credit

Course Description: R is an open-source programming language, specialized for statistical computing, and provides a variety of statistical and graphical techniques that might be relevant for any BSOS program, such descriptive statistics, linear and non-linear regression, text mining, image processing. The R language is increasingly often employed in advanced statistics and data analytics, offering a wide range of application packages for effective programming. This course introduces the R language and several powerful packages in form of lectures, worked-out examples, and group exercises. Instructor: Franz Klein. Course meets Mondays 4-6pm in LEF 0229. 

Open to all BSOS majors. Register on Testudo


BSOS331: Python Programming for the Social Sciences (Spring 2019) - 1 credit

Course Description: Python has become the most powerful programming language in advanced statistics and data analytics. It includes expansive packages for data handling and processing, including the latest developments in machine learning, and offers Integrated Development Environments (IDE) for code development, testing, debugging, and graphical representation. In addition, python is deployed on virtually all high performance computing clusters, taking advantage of multi-processing, large memory, and GPU enhanced computing environments. This course offers a thorough introduction to python and those packages that are fundamental to data processing and analysis, image processing, natural language processing, machine learning. Instructor: Franz Klein. Course meets Mondays 4-6pm in LEF 0227.

Open to all BSOS majors. Register on Testudo


Last modified
10/10/2019 - 7:23 pm