2024 Fall

DATA 200S 999 - DIS 999

Principles and Techniques of Data Science

Class #:26912

Units: 3

Instruction Mode: Online

Offered through Data Science Undergraduate Studies

Current Enrollment

Total Open Seats: -5

Enrolled: 25

Waitlisted: 0

Capacity: 20

Waitlist Max: 0

No Reserved Seats

3 hours of instructor presentation of course materials per week, 5 to 4 hours of outside work hours per week, 0 to 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

Explores the data science lifecycle: question formulation, data collection and cleaning, exploratory, analysis, visualization, statistical inference, prediction, and decision-making. Focuses on quantitative critical thinking and key principles and techniques: languages for transforming, querying and analyzing data; algorithms for machine learning methods: regression, classification and clustering; principles of informative visualization; measurement error and prediction; and techniques for scalable data processing. Research term project.

Rules & Requirements

Credit Restrictions

Students will receive no credit for DATA 200S after completing DATA C100, or DATA C200. A deficient grade in DATA 200S may be removed by taking DATA C200.