Statistical Machine Learning is used to discover patterns and relationships in large data sets. Topics will include: data exploration, classification and regression tress, random forests, clustering and association rules. Building predictive models focusing on model selection, model comparison and performance evaluation. Emphasis will be on concepts, methods and data analysis; and students are expected to complete a significant class project, individual or team based, using real-world data.

Prerequisites: PSTAT 120A-B and PSTAT 126 with a minimum grade of C or better.

4

Units

Optional

Grading

1, 2

Passtime

None

Level Limit

Letters and science

College
Unlocks PSTAT 235 PSTAT 134 PSTAT 234 PSTAT 135
These majors only finms actsc stsds stsap stats
COBURN T
Katie Coburn
3.1
63 reviews
AI predicted, based on past grading trends of the course and instructor, class info, and 127 other factors
PHELP1513
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08:00 AM - 08:50 AM
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09:00 AM - 09:50 AM
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11:00 AM - 11:50 AM
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12:00 PM - 12:50 PM
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13:00 PM - 13:50 PM
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14:00 PM - 14:50 PM
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PHELP1525
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15:00 PM - 15:50 PM
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16:00 PM - 16:50 PM
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PHELP1513
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17:00 PM - 17:50 PM
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PHELP1513
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16:00 PM - 16:50 PM
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Spring 2026 . Coburn T
TD-W 1701
T R
17:00 PM - 18:15 PM
Summer 2026 . Coburn T
HSSB 1173
M T W R
15:30 PM - 16:35 PM
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PSTAT 131 Coburn T Winter 2026 Total: 213
PSTAT 131 Yu G Fall 2025 Total: 171
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63
3.1
PSTAT131 . Coburn T A Month Ago

She's a good professor with just homeworks, section attendance, and a 50% final project. The project covers all the material from throughout the course and takes about 10-15 hours to finish. The grading is very fair, follow the rubric and you'll get an A!

1 helpful 0 unhelpful
PSTAT131 . Coburn T 8 Months Ago

131 with coburn was probably one of the best classes i've had at UCSB. you can tell she really cares about the material and how passionate she is. the project was also super useful

0 helpful 0 unhelpful
PSTAT131 . Coburn T 1 Year, 1 Month Ago

Good professor with knowledge of the subject. Straightforward in their expectations and lectures.

0 helpful 0 unhelpful
PSTAT131 . Coburn T 1 Year, 11 Months Ago

She was really organised for this class and fair and it was pretty easy to do well. 5 homeworks - one due every two weeks worth 10% each, and you were allowed submit up to two homeworks up to a week late with no penalty. Final project worth 50% which you could do on whatever and she tells you all about that right at the start.

1 helpful 0 unhelpful
PSTAT131 . Coburn T 2 Years Ago

I took Coburn for 120A my junior year and didn't love her as I felt like she didn't teach us enough. This course, on the other hand, she teaches very well. It's a lot of fun as 50% of the class is working on a final project and the rest is homeworks that help you with that project. She's genuinely fantastic at teaching this class.

0 helpful 0 unhelpful
PSTAT131 . Coburn T 2 Years Ago

She is a fantastic professor in all aspects. My only qualm with her is her unresponsiveness over email, but this is mostly because I don't go to class :)

0 helpful 0 unhelpful
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PSTAT 120A
0 / 300 Enrolled
Probability and Statistics
T B A
T R
14:00 PM - 15:15 PM
PSTAT 120B
0 / 150 Enrolled
Probability and Statistics
Amos Natido 4.1
M W
17:00 PM - 18:15 PM
PSTAT 122
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Design and Analysis of Experiments
T B A
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14:00 PM - 15:15 PM
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Regression Analysis
T B A
M W
12:30 PM - 13:45 PM
PSTAT 126
0 / 100 Enrolled
Regression Analysis
Mengyang Michael Gu 3.9
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Database Management for Data Analysis
Dawn Holmes 3.2
T R
11:00 AM - 12:15 PM