Course Schedule and Catalog
Course Schedule - Spring Semester 2025
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
DSCI 302 001 (CRN: 26662)
DATA SCIENCE TOOLS AND MODELS
Long Title: INTRODUCTION TO DATA SCIENCE TOOLS AND MODELS
Department: Data Science
Instructor: Myers, Risa
Meeting: 1:00PM - 2:15PM TR (13-JAN-2025 - 25-APR-2025)
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
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
Must be enrolled in one of the following Fields of Study:
Major: Sport Analytics
Prerequisites: COMP 140 OR DSCI 101
Section Max Enrollment: 12
Section Enrolled: 0
Total Cross-list Max Enrollment: 50
Total Cross-list Enrolled: 0
Waitlisted: 0 (Max 198)
Current members of the waitlist have priority for available seats.
Enrollment data as of: 14-NOV-2024 4:51PM
Final Exam: No Final Exam
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. Cross-list: DSCI 302. Mutually Exclusive: Cannot register for DSCI 302 if student has credit for COMP 330.