Spring 2025 Statistics GU4243 section 003

APPLIED DATA SCIENCE

Climate Pred Challenges

Call Number 14030
Day & Time
Location
T 4:10pm-6:40pm
To be announced
Points 3
Grading Mode Standard
Approvals Required None
Instructors Galen A McKinley
Tian Zheng - e-mail, homepage
Type LECTURE
Method of Instruction In-Person
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 be 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 4 students (5 max) as of 4:05PM Saturday, December 21, 2024
Subject Statistics
Number GU4243
Section 003
Division Interfaculty
Section key 20251STAT4243W003