How to Think Like a Data Scientist (CS4115.01)

Tim Schroeder

This class will cover the methods used to gather, clean, normalize, visualize, and analyze quantitative data to inform decision making in multiple fields of study. We will use spreadsheets, SQL and Python to work on real-world datasets using a combination of procedural and basic machine-learning algorithms. Students will also learn to ask good, exploratory questions and develop metrics to come up with a well thought-out analysis through work on collaborative, practical projects.

Prerequisites: Prior coursework in computer science, permission of instructor
Credits: 4
M/Th 10:00-11:50
Maximum Enrollment: 18
Course Frequency: Once a year
This course is categorized as All courses, Computer Science.