Spring 2024 Statistics GR5243 section 002

APPLIED DATA SCIENCE

Call Number 17184
Day & Time
Location
W 6:10pm-8:55pm
903 School of Social Work
Points 3
Grading Mode Standard
Approvals Required None
Instructor Ying Liu
Type LECTURE
Method of Instruction Hybrid 20-79
Course Description

Prerequisites: Pre-requisite for this course includes working knowledge in Statistics and Probability, data mining, statistical modeling and machine learning. Prior programming experience in R or Python is required. This course will incorporate knowledge and skills covered in a statistical curriculum with topics and projects in data science. Programming will covered using existing tools in R. Computing best practices will be taught using test-driven development, version control, and collaboration. Students finish the class with a portfolio of projects, and deeper understanding of several core statistical/machine-learning algorithms. Short project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications.

Web Site Vergil
Department Statistics
Enrollment 40 students (65 max) as of 9:04AM Wednesday, December 4, 2024
Subject Statistics
Number GR5243
Section 002
Division Interfaculty
Open To GSAS
Note STAT MA students only
Section key 20241STAT5243W002