The certificate highlights how big data, computational analysis, and related techniques can be used to shed light on theoretical and policy questions in the fields of public policy, public health, sociology, criminal justice, political science, economics, computer science, and network science. The certificate will contribute to students’ understanding of:
- How to collect, analyze, and interpret insights culled from applying computational analyses to big data in social science domains
- The ways in which computational analysis can be used to develop policy and evaluate policy outcomes and results
The field is new and developing rapidly, and employers are eager to hire students trained in this area—both because computational social science is at the cutting edge of interdisciplinary work and because it offers new opportunities for research and analysis. This certificate leverages the real-world relevance of big data, source data, machine learning, and predictive analytics, which are dominant aspects of the contemporary workplace landscape. The certificate is available on the Boston campus and online modalities.
- Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
- Certain options within the program may be required at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality.
Complete all courses and requirements listed below unless otherwise indicated.
Core Requirements
Course List | Code | Title | Hours |
| INSH 5301 | Introduction to Computational Statistics | 4 |
| or INSH 6406 | Analyzing Complex Digitized Data |
| INSH 5303 | Machine Learning in the Social Sciences | 4 |
| or DA 5030 | Introduction to Data Mining/Machine Learning |
Elective
Course List | Code | Title | Hours |
| 4 |
| Information Design and Visual Analytics | |
| Social Networks | |
| Geographic Information Systems for Urban and Regional Policy | |
| Big Data for Cities | |
Program Credit/GPA Requirements
12 total semester hours required
Minimum 3.000 GPA required
