This course investigates strategies behind popular computational methods used in data science. In addition, many of the algorithms are implemented using the programming language Python. No prior programming experience is required so the course presents the basics of the Python language as well as how to leverage Python’s libraries to solve real-world problems in data science. Prerequisite: MAC 1105 or equivalent.
Spring 2021 Course Overview
This course introduces the student to the programming language Python and uses it to solve real-world problems in data science. Some basic problems in data science are investigated; for example, one such problem is classification of data such as predicting whether a tumor is malignant or benign based upon characteristics of a medical image. Another example is clustering of data to see if the data can be split into groups based on underlying properties which may not be obvious to humans. Some examples of data sets which we use include Game of Thrones battles, data on common breakfast cereals, crime data, medical data sets for diabetes and cancer, botanical data, wine quality data and data from the Titanic (a luxury passenger liner which sank in 1912). The only prerequisite for this course is College Algebra; no prior programming language is required.
"I have been wanting to learn Python for a while now and I also wanted to take a class that would expand my knowledge of data analysis/data science. This class was an ideal fit for both of these desires."
"I like the Python portion a lot. Following along to the many examples done in the videos and then doing similar ones on my own in the practice notebooks is very effective. To me, everything here is good."
"I honestly feel as though you guys did a great job with the format of this class. That means everything from the grades, organization of the assignments, videos, and written notes."
"I feel like the data science portion is done well. The reading can be pretty dense but working through examples in text and videos really helped me grasp all the conceptual material."