DSCI 302 - DATA SCIENCE TOOLS AND MODELS
Long Title: INTRODUCTION TO DATA SCIENCE TOOLS AND MODELS
Department: Data Science
Grade Mode: Standard Letter
Language of Instruction: Taught in English
Course Type: Lecture
Credit Hours: 3
Restrictions: Must be enrolled in one of the following Level(s):
Undergraduate Professional
Visiting Undergraduate
Undergraduate
May not be enrolled in one of the following Department(s):
Computer Science
May not be enrolled in one of the following Major(s):
May not be enrolled in one of the following Minor(s):
Must be enrolled in one of the following Fields of Study:
Major: Sport Analytics
Minor: Data Science
Prerequisite(s): COMP 140 OR DSCI 101
Description: This course introduces key concepts in data management, preparation, and modeling and provides students with hands-on experience in performing these tasks using modern tools, including relational databases, pandas, and Spark. Models covered include kNearest Neighbors, linear regression and gradient descent. For registration purposes, DSCI 101 or COMP 140 is a required prerequisite for this course. With instructor permission, students who have experience with the Python programming language may be allowed to special register for this course. Note that these students may be required to demonstrate proficiency with Python. Priority for this course is given to students enrolled in the data science minor or sport analytics major. Other students may be permitted to enroll at the discretion of the instructor. Mutually Exclusive: Cannot register for DSCI 302 if student has credit for COMP 330.