The Data Science and Engineering minor requires 8 courses: 4 core courses, 2 studio courses, and 2 elective courses. No more than 3 courses may be double counted within a student's 16-unit major program. Courses with a grade lower than “C-” cannot be applied to the minor.
Core courses (4 units):
Data Science Studio Courses (2 units):
Elective Courses (2 units):
Course List
| Course |
Title |
| BMD_ENG 311-0 | Computational Genomics |
| BMD_ENG 395-0 | Topics in Biomedical Engineering (Biomedical Applications in Machine Learning) |
| CHEM_ENG 379-0 | Computational Biology: Analysis and Design of Living Systems |
| CIV_ENV 304-0 | Civil and Environmental Engineering Systems Analysis |
| CIV_ENV 473-0 | Survey methods, data and analysis |
| CIV_ENV 480-1 | Travel Demand Analysis & Forecasting 1 |
| CIV_ENV 480-2 | Advances in Travel Demand Analysis and Forecasting |
| CIV_ENV 495-0 | Selected Topics in Civil Engineering (Data Analytics for Transportation and Urban Infrastructure Applications) |
| COMP_SCI 348-0 | Introduction to Artificial Intelligence |
| COMP_SCI 394-0 | Agile Software Development |
| COMP_SCI 396-0 | Special Topics in Computer Science (Deep Learning) or (Interactive Information Visualization) or (Computing, Ethics, and Society) or (Visualization for Scientific Communication ) |
| COMP_SCI 397-0 | Special Projects in Computer Science (Rapid Prototyping for Software Innovation) |
| ELEC_ENG 328-0 | Information Theory & Learning |
| ELEC_ENG 335-0 | Deep Learning Foundations from Scratch |
| ELEC_ENG 373-0 | Deep Reinforcement Learning |
| ELEC_ENG 395-0 | Special Topics in Electrical Engineering (Optimization Techniques for Machine Learning and Deep Learning) |
| ELEC_ENG 424-0 | Distributed Optimization |
| ELEC_ENG 433-0 | Statistical Pattern Recognition |
| ES_APPM 345-0 | 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 472-0 | Introduction to the Analysis of RNA Sequencing Data |
| ES_APPM 479-0 | Data Driven Methods for Dynamical Systems |
| IEMS 307-0 | Quality Improvement by Experimental Design |
| IEMS 308-0 | Data Science and Analytics |
| IEMS 313-0 | Foundations of Optimization |
| IEMS 340-0 | Field Project Methods |
| IEMS 341-0 | Social Networks Analysis |
| IEMS 351-0 | Optimization Methods in Data Science |
| MAT_SCI 391-0 | Process Design |
| MECH_ENG 301-0 | Introduction to Robotics Laboratory |
| MECH_ENG 395-0 | Special Topics in Mechanical Engineering (Mechanistic Data Science) |
| MECH_ENG 441-0 | Engineering Optimization for Product Design and Manufacturing |
| MECH_ENG 469-0 | Machine Learning and Artificial Intelligence for Robotics |
| MECH_ENG 495-0 | Selected Topics in Mechanical Engg (Sensory Navigation and Machine Learning for Robotics) |