COMP 330: TOOLS & MODELS - DATA SCIENCE
Spring 2027 · Section 001 · CRN 22973
This course is an introduction to modern data science. Data science is the study of how to extract actionable, non-trivial knowledge from data. The proposed course will focus both on the software tools used by practitioners of modern data science, as well as the mathematical and statistical models that are employed in conjunction with such software tools. On the tools side, we will cover the basics of relational database systems, as well as modern systems for distributed computing based on MapReduce. On the models side, the course will cover standard supervised and unsupervised models for data analysis and pattern discovery. Can be taken concurrently with COMP 215. Cross-list: COMP 543. Recommended Prerequisite(s): COMP 330 or COMP 341 or COMP 414 or COMP 440 or DSCI 303 or ELEC 378 or ELEC 478 or CMOR 360 or CMOR 438 or STAT 413 or ECON 434 Mutually Exclusive: Cannot register for COMP 330 if student has credit for COMP 543/DSCI 302.
- Credits
- 3
- Instructors
- Risa Myers, Simon Koch