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

Program Information

The Graduate Diploma (GDip) in Computational Data Analytics for the Social Sciences and Humanities (CDASH) will train students in coding, data interpretation and visualization from a multi-disciplinary perspective that will enable them to work in teams and to communicate key findings to stakeholders in a manner that leads to actionable impacts. The GDip in CDASH will also give students different theoretical frameworks from the social sciences/humanities that will allow them to analyze societal issues relating to data collection and use by firms and governments.

Admission 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 register by completing an online registration form. The application should identify the courses that the student 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.

Diploma requirements

  • Students must 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 for the diploma and the degree.
  • 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 Decision and Wicked Problems
    • PS 699 - Coding and Programming - Special Topics 3 
    • PS xxx - Data Mining and Machine Learning (pending approval)
    • PSYCH 640 - Data Analysis and Graphing in R - Special Topics 10
    • SOC xxx - The Politics and Practices of Big Data (pending development/approval)
  • Students must maintain an average of 70% across courses for this GDip.