Spring 2026 All School of Data Science Classes Class Schedule
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SIS Description
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Foundation of Data Science
100
Foundation of Data Science
Lecture (3 Units)
Open
Brian Wright
Mo|We 02:00 PM - 03:15 PM
101
Foundation of Data Science
Laboratory (0 Units)
Waitlist
(0)
Ali Rivera
Fr 02:00 PM - 02:50 PM
Programming for Data Science
Data Science Systems
Communicating with Data
Data Ethics
Value I: Ethics & Policy in Data Science - Major
Foundations of Machine Learning
001
Foundations of Machine Learning
Lecture (3 Units)
Waitlist
(0)
Terence Johnson
Tu|Th 12:30 PM - 01:45 PM
002
Foundations of Machine Learning
Lecture (3 Units)
Open
Cheng Peng
Tu|Th 09:30 AM - 10:45 AM
003
Foundations of Machine Learning
Lecture (3 Units)
Open
Michael Freenor
Tu|Th 03:30 PM - 04:45 PM
Analytics I: Foundations of Machine Learning
Mathematics for Data Science
100
Mathematics for Data Science
Lecture (4 Units)
Open
Gianluca Guadagni
Tu|Th 11:00 AM - 12:15 PM
101
Mathematics for Data Science
Laboratory (0 Units)
Open
Gianluca Guadagni
We 01:00 PM - 01:50 PM
200
Mathematics for Data Science
Lecture (4 Units)
Closed
Gianluca Guadagni
Tu|Th 12:30 PM - 01:45 PM
Principles of Inference and Prediction
Data Science Project
Data Design II: Interactive Applications
001
Data Design II: Interactive Applications
Lecture (3 Units)
Open
Mai Dahshan
Tu|Th 12:30 PM - 01:45 PM
Value II: Explainable AI
Introduction to Deep Learning
Data by Design
Independent Study in Data Science
Text as Data
Healthcare Data Science
Don't Invent The Torment Nexus: The History of Technology & Work
Computation for Data Science
Interactive Applications
001
Interactive Applications
Lecture (3 Units)
Open
Mai Dahshan
Tu|Th 12:30 PM - 01:45 PM
Understanding Uncertainty
Deep Learning in Environmental Science
001
Deep Learning in Environmental Science
Lecture (3 Units)
Open
Antonios Mamalakis
Tu|Th 09:30 AM - 10:45 AM
Advanced Cloud Computing
Data Engineering I: Data Pipeline Architecture
Ethics of Big Data I
Data Science Capstone
Machine Learning I: Introduction to Predictive Modeling
Machine Learning II: Data Mining & Statistical Learning
Machine Learning III: Deep Learning
Computation II: Numerical Analysis & Optimization
Theory II: Inference & Prediction
Physics-Aware Deep Learning
Advanced Machine Learning II: Methods & Application
Time Series Modeling
Value I: Data Ethics, Policy and Governance
Independent Study
Design I: Human-Centered Design
Network Science
Master's Level Thesis Research
Dissertation Research