2021 Fall
INFO C8 001 - LEC 001
Formerly Computer Science C8/Statistics C8/Information C8
Foundations of Data Science
Ani Adhikari, David Wagner
Aug 25, 2021 - Dec 10, 2021
Mo, We, Fr
10:00 am - 10:59 am
Internet/Online
Class #:29347
Units: 4
Instruction Mode:
Pending Review
Offered through
School of Information
Current Enrollment
Total Open Seats:
0
Enrolled: 0
Waitlisted: 0
Capacity: 0
Waitlist Max: 0
No Reserved Seats
Hours & Workload
7 hours of outside work hours per week, 2 hours of instructional experiences requiring special laboratory equipment and facilities per week, and 3 hours of instructor presentation of course materials per week.
Final Exam
MON, DECEMBER 13TH
08:00 am - 11:00 am
Pimentel 1
Dwinelle 155
Social Sciences Building 126
Joan and Sanford I. Weill 101
Davis 534
Social Sciences Building 166
Social Sciences Building 170
Cory 247
Other classes by Ani Adhikari
Other classes by David Wagner
Course 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.
Rules & Requirements
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.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials