Students must complete the Core and Electives. All Computer Science general requirements must also be met.
Core
29-31 credits
- DSC110 - Introduction to Vectors and Matrices for Data Science or
MTH210 - Introduction to Linear Algebra
- CSC113 - Data Science for the World
- CSC115 - Python Programming for Everyone or
CSC315 - Introduction to Python for Scientists
- CSC120 - Computer Programming I
- CSC220 - Computer Programming II
- DSC344 - Principles and Practice of Data Science
- DSC345 - Principles and Practice of Artificial Intelligence
- MTH161 - Calculus I (or equivalent - MTH140 and MTH141, or MTH151, or MTH171)
- PHI115 - Social and Ethical Issues in Computing
Electives
6 approved elective credits from
Techniques
- CSC423 - Database Systems
- CSC542 - Statistical Learning with Applications
- CSC545 - Introduction to Artificial Intelligence
- CIM563 - Design with AI
- EPS351 - Introduction to Statistics and Research Design or
PSY 292 - Introduction to Biobehavioral Statistics
- EPS401 - Advanced statistics: Using regression for predictive modeling
- EPS402 - Statistical Programing in R and SAS
- JMM331 - Introduction to Infographics and Data Visualization
Applications
- CSC329 - Introduction to Game Programming
- CSC410 - Computer Science Project Planning
- CSC411 - Computer Science Project Implementation
- CSC412 - Computer Science Internship
- CSC549 - Biomedical Data Science
- GEG305 - Spatial Data Analysis I
- GEG310 - Geographic Information Systems I
- GEG405 - Spatial Data Analysis II
- GEG410 - Geographic Information Systems II
- MLL410 - Digital Literacy Through Cultural and Literary Topics
- PSY110 - Introduction to Psychology
Other courses can be approved as electives on request.
