INFO 5001
Last Updated
- Schedule of Classes - March 17, 2025 8:55AM EDT
Classes
INFO 5001
Course Description
Course information provided by the 2025-2026 Catalog.
This is an applied course for data scientists with little-to-no programming experience who wish to harness growing digital and computational resources. The focus of the course is on generating reproducible research using programming languages and version control software. Major emphasis is placed on a pragmatic understanding of core principles of programming and packaged implementations of methods. Students will leave the course with basic computational skills implemented through many computational methods and approaches to data science; while students will not become expert programmers, they will gain the knowledge of how to adapt and expand these skills as they are presented with new questions, methods, and data.
Last 4 terms offered (None)
Outcomes REF-FA25
- Construct and execute basic programs using elementary programming techniques (e.g. loops, conditional statements, user-defined functions.
- Implement data science workflows using common, reproducible methods and software tools.
- Implement statistical learning and machine learning algorithms for a range of data structures.
Regular Academic Session. Choose one lecture and one discussion.
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Credits and Grading Basis
4 Credits Opt NoAud(Letter or S/U grades (no audit))
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Class Number & Section Details
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Meeting Pattern
- TR
- Aug 25 - Dec 8, 2025
Instructors
Soltoff, B
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Additional Information
Instruction Mode: In Person
For Bowers Computer and Information Science (CIS) Course Enrollment Help, please see: https://tdx.cornell.edu/TDClient/193/Portal/Home/
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Class Number & Section Details
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Meeting Pattern
- F
- Aug 25 - Dec 8, 2025
Instructors
Soltoff, B
-
Additional Information
Instruction Mode: In Person
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