UCSBPlat.com directly in your GOLD Try it Now

Basics in distributed data storage, retrieval, processing and cloud computing. Overview of methods for analyzing big data from both high dimensional statistics and machine learning - topics chosen from penalized regression, classification/clustering, dimension reduction, random projections, kernel methods, network clustering, graph analytics, supervised and unsupervised learning among others.

Prerequisites: PSTAT 131 or PSTAT 231 or Computer Science 165B; and Computer Science 9 (preferred) or Computer Science 16. A minimum letter grade of C or better must be earned in each course.

4

Units

Optional

Grading

1, 2

Passtime

None

Level Limit

Letters and science

College
These majors only finms stsds actsc stsap stats
OH SANG-YUN
Sang-Yun Oh
2.3
29 reviews
PHELP1513
M
16:00 PM - 16:50 PM
20 / 20 Full

PHELP1513
M
12:00 PM - 12:50 PM
20 / 20 Full

PHELP1513
M
13:00 PM - 13:50 PM
20 / 20 Full

PHELP1513
M
14:00 PM - 14:50 PM
20 / 20 Full

PHELP1513
M
15:00 PM - 15:50 PM
20 / 20 Full

Winter 2024 . Oh Sang-Yun
NH 1006
T R
15:30 PM - 16:45 PM
See All
PSTAT 135 Oh Sang-Yun Spring 2025 Total: 96
PSTAT 135 Oh Sang-Yun Winter 2024 Total: 100
See All
29
2.3
PSTAT135 . Oh Sang-Yun 5 Months Ago

Sang is a considerate professor, and taught the course content in a useful, albeit monotonous fashion. A lot of new content to cover than most PSTAT courses, with weekly quizzes in lecture (open note!) and pointless sections, and while assignments were certainly doable some programs chosen were quite difficult to work with (especially the project).

0 helpful 0 unhelpful
PSTAT135 . Oh Sang-Yun 5 Months Ago

Lectures were very slow and dry. Content seemed disorganized and jumped around topics week by week. Quiz every Thursday in person at the end of class. And there was a final group project, but it was just really tedious because of the online system we had to use. Overall very disappointing for a class I thought would be really interesting.

0 helpful 0 unhelpful
PSTAT134 . Oh Sang-Yun 8 Months Ago

Very bad and boring lectures. Do not take this professor if you actually want to learn anything.

0 helpful 0 unhelpful
PSTAT134 . Oh Sang-Yun 1 Year, 7 Months Ago

the way the class is weighted it is easy to get a good grade without doing that much however class was so boring i did not learn anything in class and I was confused all quarter long. I came away from this class feeling like I learned absolutely nothing.

0 helpful 0 unhelpful
PSTAT126 . Oh Sang-Yun 1 Year, 10 Months Ago

Oh has a unique talent for ignoring student feelings and never bothers with such trivial matters as seeing things from their perspective. Truly, a 'remarkable' choice for anyone seeking an 'unforgettable' learning experience. Highly 'recommended' for those who appreciate the finer nuances of educational indifference.

0 helpful 0 unhelpful
PSTAT126 . Oh Sang-Yun 1 Year, 10 Months Ago

He has a unique talent for ignoring student feelings and never bothers with such trivial matters as seeing things from their perspective. Truly, a 'remarkable' choice for anyone seeking an 'unforgettable' learning experience. Highly 'recommended' for those who appreciate the finer nuances of educational indifference.

0 helpful 0 unhelpful
See all 29 reviews
PSTAT 122
121 / 125 Enrolled
Design and Analysis of Experiments
Peter Chi 4.9
M W
09:30 AM - 10:45 AM
52.8% A
PSTAT 126
100 / 100 Full
Regression Analysis
Puja Pandey 4.3
T R
11:00 AM - 12:15 PM
42.9% A
PSTAT 126
100 / 100 Full
Regression Analysis
Puja Pandey 4.3
T R
09:30 AM - 10:45 AM
42.9% A
PSTAT 130
125 / 125 Full
SAS Base Programming
Julie Swenson 4.3
T
08:00 AM - 09:15 AM
35.7% A
PSTAT 131
100 / 100 Full
Introduction to Statistical Machine Learning
Katie Coburn 3.3
T R
12:30 PM - 13:45 PM
58.5% A
PSTAT 134
65 / 80 Enrolled
Statistical Data Science
Laura Baracaldo 1.8
T R
12:30 PM - 13:45 PM
55.0% A