Call Number | 17757 |
---|---|
Day & Time Location |
W 6:10pm-8:55pm 425 Pupin Laboratories |
Points | 3 |
Grading Mode | Standard |
Approvals Required | None |
Instructor | Ying Liu |
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 | 7 students (10 max) as of 5:08PM Saturday, September 7, 2024 |
Subject | Statistics |
Number | GU4243 |
Section | 002 |
Division | Interfaculty |
Section key | 20241STAT4243W002 |