COMP 330 - TOOLS & MODELS - DATA SCIENCE
Long Title: TOOLS AND MODELS FOR DATA SCIENCE
Department: Computer Science
Grade Mode: Standard Letter
Language of Instruction: Taught in English
Course Type: Lecture
Credit Hours: 3
Must be enrolled in one of the following Level(s):
Prerequisite(s): (MATH 211 OR MATH 212 OR MATH 221 OR MATH 222 OR MATH 232) AND COMP 215
Description: 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. Graduate/Undergraduate Equivalency: COMP 543. Mutually Exclusive: Cannot register for COMP 330 if student has credit for COMP 543/DSCI 302.