CS C8. Foundations of Data Science

Catalog Description: Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.

Units: 4.0

Prerequisites: This course may be taken on its own, but students are encouraged to take it concurrently with a data science connector course (numbered 88 in a range of departments).

Credit Restrictions: Students will receive no credit for DATA C8\COMPSCI C8\INFO C8\STAT C8 after completing COMPSCI 8, or DATA 8. A deficient grade in DATA C8\COMPSCI C8\INFO C8\STAT C8 may be removed by taking COMPSCI 8, COMPSCI 8, or DATA 8.

Formats:
Fall: 3.0-3.0 hours of lecture and 2.0-2.0 hours of laboratory per week
Spring: 3.0-3.0 hours of lecture and 2.0-2.0 hours of laboratory per week
Summer: 6.0 hours of lecture and 4.0 hours of laboratory per week

Grading basis: letter

Final exam status: Written final exam conducted during the scheduled final exam period

Also listed as: DATA C8, STAT C8, INFO C8


Class Schedule (Fall 2020):
MoWeFr 11:00AM - 11:59AM, Internet/Online – An Ju, Ananya Krishnan, David WAGNER, Sam Wu, Swupnil Sahai, Tamara Vilaythong

Class homepage on inst.eecs

General Catalog listing