DACSS Curriculum
The Master's of Science degree in Data Analytics and Computational Social Science (MS in DACSS) degree curriculum has been carefully designed to prepare students for the workforce and reflects current industry standards for data science professionals. The MS in DACSS degree requires satisfactory completion of 12 courses, totaling 34 credits. The curriculum is made up of 8 core courses and 4 elective courses.
Core courses at DACSS include:
- 1 preparatory course: DACSS 600 Essential Math for Applied Data Science, which sets students up for success by reviewing key algebraic skills and providing a gentle background in probability, matrix algebra, and basic calculus concepts. Students with sufficient mathematical preparation may request to replace this with an elective of their choice. Sample Syllabus
- 3 foundational courses: DACSS 601, 602, and 603, which cover essential data science skills in programming, research design, and statistical reasoning, ensuring that students have a shared knowledge base and are set up for success in their chosen advanced core course and technical electives.
- DACSS 601: Data Science Fundamentals
This course provides students with an introduction to the R programming language. Sample Syllabus - DACSS 602: Research Design
This course introduces students to the basic language of behavioral research. Sample Syllabus - DACSS 603: Introduction to Quantitative Analysis
This course provides a rigorous introduction to quantitative empirical research methods. Sample Syllabus
- DACSS 601: Data Science Fundamentals
- 1 advanced methods course: This provides students with cutting-edge training in advanced analytical methods, either through DACSS 713 Advanced Statistical Methods or DACSS 756 Machine Learning for Social Sciences.
- 2 professional development courses: DACSS 691P Polishing your Professional Presence (2 credits) & DACSS 621 Ethics of Data Science and AI (2 credits).
- 1 capstone research project course: Choose from either DACSS 684 Advanced Data-Driven Storytelling, an online course that provides students with an opportunity to sharpen their skills in providing clear, professional, data-driven communication, or DACSS 698R Practicum - Research Lab, an in-person collaborative course with possible faculty-mentored, client-based, and/or team projects. Please note that DACSS 684 and DACSS 698R are only offered in fall and spring semesters.
DACSS students also develop advanced technical skills through taking our technical elective courses, and we also encourage students to deepen their subject matter expertise and content knowledge through optional substantive elective courses taken across campus.
2 technical electives, of which at least one must be from our advanced technical list, allowing students to build advanced, specialized skills appropriate for their career path.
2 additional technical or substantive electives that may be taken within or outside the DACSS program that allow students to further their technical skills or substantive knowledge as appropriate for their professional goals.
Suggested Timelines
The MS in DACSS is a flexible program that is designed to meet the needs of every learner. Whether you're full-time, part-time, in-person or online, DACSS is built to support your development. Learn about our different suggested course timelines here.
Optional DACSS Concentrations
The DACSS Field Experience concentration is designed for students who wish to complete an internship or co-op for academic credit. This concentration will appear on your transcript upon graduation from the program. Please see Suggested Timelines for the Field Experience timeline.
Students who began the DACSS program prior to Summer 2026, please see your degree requirements on the Academic and Career Advising page.