INFO 5001

INFO 5001

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.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 4 Credits Opt NoAud

  •  7327 INFO 5001   LEC 001

    • TR
    • Aug 25 - Dec 8, 2025
    • Soltoff, B

  • Instruction Mode: In Person

    For Bowers Computer and Information Science (CIS) Course Enrollment Help, please see: https://tdx.cornell.edu/TDClient/193/Portal/Home/

  •  7328 INFO 5001   DIS 201

    • F
    • Aug 25 - Dec 8, 2025
    • Soltoff, B

  • Instruction Mode: In Person

  •  9145 INFO 5001   DIS 202

    • F
    • Aug 25 - Dec 8, 2025
    • Soltoff, B

  • Instruction Mode: In Person