INTERMEDIATE DATA SCIENCE
INTERMEDIATE DATA SCIENCE
2020 Fall Term
3 Units
Computer Science 310
This course introduces intermediate data science and its implementation using R and Python, with applications in natural and social science, public health and welfare, and other areas. Students will explore methods of data analysis, cleaning, simulation and visualization and machine learning. Prior knowledge of programming and statistical analysis is assumed.
Other Requirements: PREREQ: COMPSCI 170 AND (COMPSCI 180 OR COMPSCI 220 OR COMPSCI 222) AND 1 COURSE IN STATISTICS (BIOLOGY 303 OR ECON 245 OR MATH 230 OR MATH 342 OR PSYCH 215 OR SOCIOLGY 295 OR SOCWORK 250), OR PERMISSION OF INSTRUCTOR
Class Schedule
Disclaimer
- This schedule is informational and does not guarantee availability for registration.
- Sections may be full or not open for registration. Please use WINS if you wish to register for a course.
| Section Details | Meeting Details & Topic | Instructor | Syllabus | ||
|---|---|---|---|---|---|
|
01-LEC 3548
3 Units
|
09/02 - 12/11 (1) |
Robert Kuzoff
|
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| WEB BASED | |||||
| This is a web based course using Canvas. Further information will be given before the first day of class. Required additional fee of $50 per credit will be assessed for this class. | |||||
