DATASCI 112: Principles of Data Science
A hands-on introduction to the methods of data science. Strategies for analyzing and visualizing tabular data, including common patterns and pitfalls. Data acquisition through web scraping and REST APIs. Core principles of machine learning: supervised vs. unsupervised learning, training vs. test error, hyperparameter tuning, and ensemble methods. Introduction to data of different shapes and sizes, including text, image, and geospatial data. The focus is on intuition and implementation, rather than theory and math. Implementation is in Python and Jupyter notebooks, using libraries such as pandas and scikit-learn. Course culminates in a final project where students apply the methods to a data science problem of their choice. Prerequisite:
CS 106A or equivalent programming experience in Python. (Students with experience in another programming language should take
CS 193Q to catch up on Python.)
Terms: Win, Spr, Sum
| Units: 5
| UG Reqs: WAY-AQR
DATASCI 196: Teaching Data Science
Students practice data science concepts and communication by leading a discussion section of an introductory data science course. Weekly meetings address best teaching practices. When taken for 3 units and a letter grade, counts as a technical elective for the B.S. in Data Science. Enrollment limited to students selected as a CA for an introductory data science course. Application here:
https://forms.gle/DcL7imUex7CQGbfa9
Terms: Sum
| Units: 1-3
| Repeatable
4 times
(up to 12 units total)
Instructors:
Sun, D. (PI)
DATASCI 198: Practical Training
For students majoring in Data Science only. Students obtain employment in a relevant industrial or research activity to enhance their professional experience. Students may enroll in Summer Quarters only and for a total of three times. Students must first notify their DS adviser before enrolling in their course section, and must submit a one-page written final report summarizing the knowledge/experience gained upon completion of the internship in order to receive credit.Please notes that F-1 international students enrolled in their department¿s CPT course cannot start working without first obtaining a CPT-endorsed I-20 from Bechtel International Center (enrolling in the CPT course alone is insufficient to meet federal immigration regulations).
Terms: Win, Spr, Sum
| Units: 1
| Repeatable
4 times
(up to 4 units total)
Instructors:
Nobles, M. (PI)
;
Sun, D. (PI)
DATASCI 199: Independent Study
For undergraduates.
Terms: Aut, Win, Spr, Sum
| Units: 1-6
| Repeatable
20 times
(up to 300 units total)
Instructors:
Duchi, J. (PI)
;
Kim, G. (PI)
;
Sabatti, C. (PI)
...
more instructors for DATASCI 199 »
Instructors:
Duchi, J. (PI)
;
Kim, G. (PI)
;
Sabatti, C. (PI)
;
Salgado, R. (PI)
;
Sun, D. (PI)
;
Walther, G. (PI)
;
Weinstein, J. (PI)
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