Call Number | 13358 |
---|---|
Day & Time Location |
W 6:10pm-8:55pm 142 Uris Hall |
Points | 3 |
Grading Mode | Standard |
Approvals Required | None |
Instructors | Ying Liu 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 | 14 students (25 max) as of 7:26PM Sunday, April 27, 2025 |
Subject | Statistics |
Number | GU4243 |
Section | 001 |
Division | Interfaculty |
Open To | Barnard College, Columbia College, Engineering:Undergraduate, Engineering:Graduate, GSAS, General Studies, Professional Studies |
Section key | 20233STAT4243W001 |