Students must complete the Core, Techniques, and Applications requirements. All Computer Science general requirements must also be met.
Core (40 credits)
Computer Science (23 credits)
- CSC113 - Data Science for Everyone
- CSC120 - Computer Programming I
- CSC220 - Computer Programming II
- CSC315 - Introduction to Python for Scientists
- CSC317 - Data Structures and Algorithm Analysis
- CSC545 - Introduction to Artificial Intelligence
- CSC546 - Introduction to Machine Learning with Applications
Mathematics (17 credits)
- MTH161 - Calculus I (or equivalent - MTH140 and MTH141, or MTH151, or MTH171)
- MTH162 - Calculus II (or equivalent - MTH172)
- MTH210 - Introduction to Linear Algebra
- MTH224 - Introduction to Probability and Statistics
- MTH309 - Discrete Mathematics
Techniques (9 credits)
- CSC115 - Python Programming for Everyone (only if taken before CSC 120)
- CSC322 - System Programming
- CSC423 - Database Systems
- CSC506 - Logic and Automated Reasoning
- CSC542 - Statistical Learning with Applications
- CIM563 - Design with Al
- ECE553 - Neural Networks
- ECE574 - Agent Technology
- EPS351 - Introduction to Statistics and Research Design
- EPS401 - Advanced statistics: Using Regression for Predictive Modeling
- EPS402 - Statistical Programing in R and SAS
- JMM331 - Introduction to Infographics and Data Visualization
- JMM429 - Advanced Infographics and Data Visualization
- MTH524 - Introduction to Probability
- MTH525 - Introduction to Mathematical Statistics
- MTH542 - Statistical Analysis
- PHI330 - Ethics
- PSY292 - Introduction to Biobehavioral Statistics (not permitted with MTH524, MTH525, or MTH542)
Applications (9 credits)
- CSC329 - Introduction to Game Programming
- CSC410 - Computer Science Project Planning
- CSC411 - Computer Science Project Implementation
- CSC412 - Computer Science Internship
- CSC549 - Biomedical Data Science
- CSC550 - Computational Neuroscience
- APY313 - Data Science of Culture and Language
- GEG305 - Spatial Data Analysis I
- GEG310 - Geographic Information Systems I
- GEG405 - Spatial Data Analysis II
- GEG410 - Geographic Information Systems II
- PSY110 - Introduction to Psychology
- PSY290 - Introduction to Research Methods
Other courses can be approved as techniques and applications on request.
Ethics Requirement
The Data Science & Artificial Intelligence major requires completion of the Ethics course PHI115 - Social and Ethical Issues in Computing.
