2020 Fall COMPSCI C100 999 DIS 999

2020 Fall

COMPSCI C100 999 - DIS 999

Formerly Statistics C100/Computer Science C100

Principles & Techniques of Data Science

Aug 26, 2020 - Dec 11, 2020
12:00 am
Internet/Online
Class #:33474
Units: 4

Instruction Mode: Remote Instruction
Asynchronous Instruction
Semester in the Cloud

Current Enrollment

Total Open Seats: 0
Enrolled: 0
Waitlisted: 0
Capacity: 0
Waitlist Max: 0
No Reserved Seats
Also offered as: COMPSCI C100, DATA C100

Hours & Workload

3 hours of instructor presentation of course materials per week, 7 hours of outside work hours per week, 1 hours of instructional experiences requiring special laboratory equipment and facilities per week, and 1 hours of the exchange of opinions or questions on course material per week.

Course Catalog Description

In this course, students will explore the data science lifecycle, including question formulation, data collection and cleaning, exploratory data analysis and visualization, statistical inference and prediction​, and decision-making.​ This class will focus on quantitative critical thinking​ and key principles and techniques needed to carry out this cycle. These include languages for transforming, querying and analyzing data; algorithms for machine learning methods including regression, classification and clustering; principles behind creating informative data visualizations; statistical concepts of measurement error and prediction; and techniques for scalable data processing.

Rules & Requirements

Credit Restrictions

Students will receive no credit for DATA C100\STAT C100\COMPSCI C100 after completing DATA 100. A deficient grade in DATA C100\STAT C100\COMPSCI C100 may be removed by taking DATA 100.

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.

Textbook Lookup

Guide to Open, Free, & Affordable Course Materials

eTextbooks

Associated Sections