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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information. | |
Spring 2022 Statistics GR5243 section 002 APPLIED DATA SCIENCE Climate Pred Challenges | |
| Call Number | 17317 |
| Day & Time Location |
T 4:10pm-6:40pm 903 School of Social Work |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructors | Tian Zheng - e-mail, homepage Galen A McKinley |
| 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 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 | 21 students (30 max) as of 5:04PM Wednesday, July 6, 2022 |
| Subject | Statistics |
| Number | GR5243 |
| Section | 002 |
| Division | Interfaculty |
| Campus | Morningside |
| Note | MA STAT, MSDS, DEES and E&EE. Instructor permission. |
| Section key | 20221STAT5243W002 |
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