INFO 2950

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INFO 2950

Course information provided by the Courses of Study 2023-2024.

INFO 2950 is an applied introductory course on the foundations of data science, focusing on using data to identify patterns, evaluating the strength and significance of relationships, and generating predictions using data. Topics covered include the core principles of statistical programming (such as data frames, Python/R packages, reproducible workflows, and version control), univariate and multivariate statistical analysis of small and medium-size datasets, regression methods, hypothesis testing, probability models, basic supervised and unsupervised machine learning, data visualization, and network analysis. Students will learn how to use data to make effective arguments in a way that promotes the ethical usage of data. Students who complete the course will be able to produce meaningful, data-driven analyses of real-world problems and will be prepared to begin more advanced work in data-intensive domains.

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

  •  9753 INFO 2950   LEC 001

    • TR Olin Hall 155
    • Jan 22 - May 7, 2024
    • Soltoff, B

  •  9756 INFO 2950   DIS 201

    • F Upson Hall 222
    • Jan 22 - May 7, 2024
    • Soltoff, B

  •  9758 INFO 2950   DIS 203

  •  9759 INFO 2950   DIS 204

  •  9761 INFO 2950   DIS 206

    • F Statler Hall 341
    • Jan 22 - May 7, 2024
    • Soltoff, B

  •  9762 INFO 2950   DIS 207

    • F Upson Hall 102
    • Jan 22 - May 7, 2024
    • Soltoff, B

  •  9763 INFO 2950   DIS 208

  •  9764 INFO 2950   DIS 209