Bachelor of Science in Data Science & Artificial Intelligence

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.

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