INFO 2950

INFO 2950

Course information provided by the Courses of Study 2022-2023.

Teaches basic mathematical methods for information science, with applications to data science. Topics include discrete probability, Bayesian methods, graph theory, power law distributions, Markov models, and hidden Markov models. Uses examples and applications from various areas of information science such as the structure of the web, genomics, social networks, natural language processing, and signal processing. Assignments require python programming.  

When Offered Fall.

Prerequisites/Corequisites Prerequisite: MATH 1710 or equivalent, CS 1110 or CS 1112, or permission of instructor.

Distribution Category (MQR-AS, SDS-AS)

Comments Information Science majors must complete this class prior to their senior year.

View Enrollment Information

Syllabi: none
  •   Three Week - First.  Choose one lecture and one discussion.

  • 4 Credits Graded

  •  1270 INFO 2950   LEC 001

    • MTWRF Upson Hall 146
    • May 30 - Jun 16, 2023
    • Soltoff, B

    • MTWRF Upson Hall 146
    • May 30 - Jun 16, 2023
  • Instruction Mode: In Person
    This Summer Session class is offered by the School of Continuing Education and Summer Sessions. For details visit http://www.sce.cornell.edu/ss/courses/courses.php?v=3525

  •  1271 INFO 2950   DIS 201

    • MTWRF Upson Hall 146
    • May 30 - Jun 16, 2023
    • Soltoff, B

  • Instruction Mode: In Person
    This Summer Session class is offered by the School of Continuing Education and Summer Sessions. For details visit http://www.sce.cornell.edu/ss/courses/courses.php?v=3525