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
  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 4 Credits Graded

  • 17909 INFO 2950   LEC 001

    • TR Olin Hall 155
    • Jan 23 - May 9, 2023
    • Soltoff, B

  • Instruction Mode: In Person
    Please add yourself to the waitlist via this link: https://cornell.ca1.qualtrics.com/jfe/form/SV_cFIXBRMpcbMLaCO

  • 17920 INFO 2950   DIS 201

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  • 17921 INFO 2950   DIS 202

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  • 17922 INFO 2950   DIS 203

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  • 17923 INFO 2950   DIS 204

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  • 17924 INFO 2950   DIS 205

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  • 17925 INFO 2950   DIS 206

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  • 17926 INFO 2950   DIS 207

  • Instruction Mode: In Person

  • 17927 INFO 2950   DIS 208

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  • 17928 INFO 2950   DIS 209

    • F Upson Hall 222
    • Jan 23 - May 9, 2023
    • Soltoff, B

  • Instruction Mode: In Person