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.

COMP 680 901 (CRN: 22593)

STATS COMPUTING DATA SCIENCE

Long Title: STATISTICS FOR COMPUTING AND DATA SCIENCE
Department: Computer Science
Instructor: Fagan, Mike
Meeting: 8:00PM - 9:25PM T (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: Online
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
 
Restrictions:
Must be enrolled in one of the following Program(s):
Online Master Computer Science
Online Master of Data Science
Master of Data Science
Must be enrolled in one of the following Level(s):
Graduate
Section Max Enrollment: 25
Section Enrolled: 0
Enrollment data as of: 14-NOV-2024 12:00PM
 
Additional Fees: None
 
Final Exam: GR Course-Dept Schedules Exam
 
Description: Probability and statistics are essential tools in computer science and data science. They are at the heart of areas such as efficiency analysis of algorithms and randomized algorithms and central to fields like bioinformatics, social informatics, and, of course, machine learning. Furthermore, probability and statistics are essential for data science, as they are the foundation for quantifying uncertainty and assessing support for hypotheses and derived models. This course covers topics in probability and statistics, including probability and random variables, basic stochastic processes, basic descriptive statistics, and various methods for statistical inference and measuring support. In order to enroll in an online section of this course, you are expected to have a working camera and microphone. During class sessions, you must be able to participate using your microphone and you are expected to have your camera on for the duration of the class so that you are visible to the instructor and other students in the class, just as you would be in an in-person class.