Graduate Diploma (GDip) in Computational Data Analytics for the Social Sciences and Humanities

The program information below was valid for the spring 2022 term (May 1, 2022 - August 31, 2022). This is the archived version; the most up-to-date program information is available through the current Graduate Studies Academic Calendar.

The Graduate Studies Academic Calendar is updated 3 times per year, at the start of each academic term (January 1, May 1, September 1). Graduate Studies Academic Calendars from previous terms can be found in the archives.

Students are responsible for reviewing the general information and regulations section of the Graduate Studies Academic Calendar.

Program information

  • Delivery mode 
    • On-campus
  • Program type 
    • Diploma
  • Study option(s) 

Admission requirements

  • Minimum requirements 
    • The Graduate Diploma (GDip) in Computational Data Analytics for the Social Sciences and Humanities is offered in conjunction with any University of Waterloo master’s or doctoral program.
    • Students may apply by completing an online application form, available from the Department of Economics website. The application must identify the courses that students would like to take in fulfillment of the GDip requirements. Students will receive an admission decision from the Program Director.
    • Students must be in good standing in their home master’s or doctoral program to take courses for the GDip in Computational Data Analytics for the Social Sciences and Humanities.

Degree requirements

    Coursework option:

  • Courses 
    • In order to obtain the GDip in Computational Data Analytics for the Social Sciences and Humanities, students must successfully complete 3 graduate level courses (0.50 unit weight) in addition to the degree requirements of their home master’s or doctoral program. There can be no double counting of courses for different degrees/diplomas.
    • Students must complete 3 of the following 12 courses (or other courses that fit with the goals of this GDip, as approved by the Program Director):
      • ANTH xxx Critical Data Studies: Making and Using Data in Society (pending development/approval)
      • ECON 526 Fundamentals in Programming for Big Data Analysis (pending approval)
      • ECON 625 Numerical Methods for Economists
      • ECON 626 Machine Learning for Economists
      • GEOG 606 Scientific Data Wrangling
      • HIST 640 Digital History
      • INTEG 640 Computational Social Science
      • INTEG 641 Hard Decisions and Wicked Problems
      • PS 699 Special Topics: Topic 3 Coding and Programming
      • PS xxx Data Mining and Machine Learning (pending approval)
      • PSYCH 640 Special Topics in Psychology: Topic 10 Data Analysis & Graphing in R
      • SOC xxx The Politics & Practices of Big Data (pending development/approval)
    • Students must maintain an average of 70% across courses for this GDip.
  • Link(s) to courses