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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.


Fall 2022 Statistics GR5243 section 001
APPLIED DATA SCIENCE

Call Number 13841
Day & Time
Location
W 6:10pm-8:55pm
142 Uris Hall
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 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 35 students (56 max) as of 5:33PM Monday, September 26, 2022
Subject Statistics
Number GR5243
Section 001
Division Interfaculty
Open To GSAS
Campus Morningside
Note STAT MA Students only
Section key 20223STAT5243W001

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SIS update 09/26/22 17:33    web update 09/26/22 21:16