Overview of data science key concepts and the use of tools for data retrieval, analysis, visualization, and reproducible research in preparation for advanced data science courses. Topics include an introduction to inference and prediction, principles of measurement, missing data, and notions of causality, statistical traps, and concepts in data ethics and privacy.

Prerequisites: PSTAT 120A; CS 9 or CS 16; and Math 4A, all with letter grade C or better.

4

Units

Optional

Grading

1

Passtime

None

Level Limit

Letters and science

College
These majors only prsds finms stsds actsc
ZHANG T
No info found
PHELP1513
R
09:00 AM - 09:50 AM
4 / 25

ILP 4207
R
10:00 AM - 10:50 AM
10 / 25

PHELP1518
R
14:00 PM - 14:50 PM
25 / 25 Full

ILP 4209
R
15:00 PM - 15:50 PM
20 / 25

PHELP1513
R
16:00 PM - 16:50 PM
4 / 25

PHELP1517
R
17:00 PM - 17:50 PM
8 / 25

See All
Fall 2025 . Zhang T
BUCHN1940
M W
08:00 AM - 09:15 AM
Winter 2026 . Zhang T
CHEM 1171
M W
08:00 AM - 09:15 AM
See All
PSTAT 100 Zhang T Winter 2026 Total: 107
PSTAT 100 Zhang T Fall 2025 Total: 90
PSTAT 115
49 / 75 Enrolled
Introduction to Bayesian Data Analysis
Brian Wainwright 3.1
M W
09:30 AM - 10:45 AM
PSTAT 120A
26 / 50 Enrolled
Probability and Statistics
T B A
T R
09:30 AM - 10:45 AM
PSTAT 120A
100 / 200 Enrolled
Probability and Statistics
T B A
T R
14:00 PM - 15:15 PM
PSTAT 120B
84 / 90 Enrolled
Probability and Statistics
Amos Natido 4.1
M W
14:00 PM - 15:15 PM
PSTAT 120B
16 / 150 Enrolled
Probability and Statistics
Amos Natido 4.1
M W
17:00 PM - 18:15 PM
PSTAT 120C
93 / 125 Enrolled
Probability and Statistics
Jack Miller 4.7
M W
11:00 AM - 12:15 PM