Curriculum
2026-2027 Course Listings

Programming Foundations (1 credit)

Note that you only need to take one of the following courses to fulfill the Programming Foundations requirement.

Course Course Title Fall 2026 Winter 2027 Spring 2027
COMP_SCI 150 Fundamentals of Computer Programming 1.5 MWF 12:00-12:50 (2 sections) Geisler MWF 11-11:50
Geisler
OR GEN_ENG 150 Programming for Engineers MWF 12:00-12:50 or 1:00-1:50 Sood MWF 1-1:50
Bain		 MWF 12-12:50 or 1-1:50
Bain
OR GEN_ENG 151 Honors Programming for Engineers MWF 2:00-2:50 (2 sections) Bain

Statistics Foundations (1 credit)

Course Course Title Fall 2026 Winter 2027 Spring 2027
BMD_ENG 220 (no longer offered) Introduction to Biomedical Statistics
CHEM_ENG 312 Probability and Statistics for Chemical Engineering MWF 2:00
Dallbauman
CIV_ENV 306 Uncertainty Analysis MWF 12:00-12:50 (Discussion: T 12:30-1:20)
Chen
GEN_ENG 231 Probability and Statistics for Engineers MTWF 9:00-9:50 Olds
MTWF 11:00-11:50 or 2:00-2:50 Chan 		 MTWF 9:00-9:50 Ankenman
MTWF 10:00-10:50 Ankenman
MTWF 2:00-2:50 Sadeghiamirshahidi		 MTWF 10-10:50 Wilson MTWF 11-11:50 Wilson MTWF 2-2:50 Grosof
MTWF 3-3:50 Sadeghiamirshahidi
IEMS 201 (no longer offered) Introduction to Statistics
IEMS 303 Statistics MWF 9:00-9:50
Nelson
(Lab: W 2:00, 3:00, 5:00)
MATH 314 Probability and Statistics for Econometrics MWF 2:00
Burslem
STAT 320-2 Statistical Theory & Methods 2 MWF 12:00-12:50 or 2:00-2:50
W. Jiang

Specialization (4 credits)

Course Course Title Fall 2026 Winter 2027  Spring 2027 
COMP_SCI 180, formerly 111 Software Design & Composition MWF 1-1:50 
Horswill		 MWF 1-1:50
Horswill & Riesbeck
COMP_SCI 208, formerly 214 Data Structures and Algorithms TTH 11:00-12:20 (2 sections)
St-Amour		 TTH 11:00-12:20 (2 sections)
St-Amour
COMP_SCI 217 Data Management and Information Processing TTH 9:30-10:50 Hu TuTh 2-3:20
Hummel
COMP_SCI 348 Intro to Artificial Intelligence TTH 2:00-3:20 Birnbaum TuTh 2-3:20
Rubenstein & Alexander		 TuTh 11-12:20
Elkind
COMP_SCI 349 Machine Learning TTH 9:30 - 10:50 Wood-Doughty TTH 9:30 - 10:50 Wood-Doughty TuTh 11-12:20
Alam
DATA ENG 200 Foundations of Data Science TTh 9:30-10:50
Chan		 TTh 12:30-1:50
Staff
DATA ENG 300 Data Engineering Studio TTh 9:30-10:50
(with Lab W 4:00, 5:00)
Chan
IEMS 301 Introduction to Statistical Learning MWF 12:00-12:50
Sadeghiamirshahidi
IEMS 304 Statistical Learning for Data Analysis MWF 1:00-1:50
Chen
(Lab: F 10:00-10:50, 11:00-11:50)		 MWF 1:00-1:50
Apley
(Lab: F 9:00, 10:00)		 MWF 1:00-1:50
Chen
(Lab: F 2:00, 3:00)

MLDS Electives (2 credits)

Course Course Title Fall 2026 Winter 2027 (TBD) Spring 2027 (TBD)
BMD_ENG 311 (no longer offered) Computational Genomics
BMD_ENG 312 Biomedical Applications in Machine Learning
BMD_ENG 313 (no longer offered) Wearable Devices
CHEM_ENG 379 Computational Biology
CIV_ENV 304 Systems Analysis
CIV_ENV 374 Data Science for Urban Systems
CIV_ENV 377 Choice Modeling in Engineering
CIV_ENV 474 Data Analytics for Transportation and Urban Infrastructure Applications
CIV_ENV 480-1 Travel Demand Analysis and Forecasting 1
COMP_SCI 332 Online Markets
COMP_SCI 333 Interactive Information Visualization
COMP_SCI 353 Natural & Artificial Vision TTH 11:00-12:20
Alexander
COMP_SCI 374 Causal Graphical Models
COMP_SCI 392 Rapid Prototyping for Software Innovation MWF 3:00-3:50
Riesbeck
COMP_SCI 394 Agile Software Development
COMP_SCI 396 Computing, Ethics, and Society
COMP_SCI 397 Seminar in Statistical Language Modeling
COMP_SCI 449 Deep Learning TTH 11:00-12:20 Demeter
COMP_SCI 496 Visualization for Scientific Communication
DATA ENG 300 Data Engineering Studio
ELEC_ENG 328 Information Theory and Learning
ELEC_ENG 335 Deep Learning Foundations
ELEC_ENG 373 Deep Reinforcement Learning
ELEC_ENG 395 Optimization Techniques for Machine Learning  
ELEC_ENG 424 Distributed Optimization TTH 12:30-1:50 Wei
ELEC_ENG 433 Statistical Pattern Recognition
ES_APPM 345 Applied Linear Algebra
ES_APPM 375-1 Quantitative Biology I: Experiments, Data, Models, and Analysis
ES_APPM 375-2 Quantitative Biology II: Experiments, Data, Models, and Analysis
ES_APPM 472 Introduction to the Analysis of RNA Sequencing Data MW 3:30-4:50
Kath
ES_APPM 479 Data Driven Methods for Dynamical Systems
IEMS 305 Foundations of Modern Machine Learning
IEMS 307 Quality Improvement by Experimental Design
IEMS 308 (no longer offered) Data Science and Analytics
IEMS 313 Foundations of Optimization MWF 11:00-11:50
Morton
(Lab: M 4:00-4:50, 5:00-5:50)
IEMS 340 Qualitative Methods in Engineering Systems TTH 2:00-3:20 (Lab: W 5:00-5:50)
Mejía
IEMS 341 Social Network Analysis
IEMS 351 Optimization Methods in Data Science
IEMS 352 Foundations of Generative AI & Reasoning Systems
MAT_SCI 358 Modeling and Simulation in Material Science
MAT_SCI 390-1 Process and Experimental Design
MECH_ENG 301 Introduction to Robotics Laboratory
MECH_ENG 329  Mechanistic Data Science
MECH_ENG 341 Computational Methods for Engineering Design
MECH_ENG 441 Engineering Optimization for Product Design and Manufacturing
MECH_ENG 469 Machine Learning and Artificial Intelligence for Robotics
MECH_ENG 495 Sensing Navigation and Machine Learning for Robotics

Course Listing Archive

For course listings in previous years, visit the archived pages below:

2025-2026 Course Listings

2024-2025 Course Listings