Data Science and Engineering Minor

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):

Course Title
Statistics Foundations (1 course)
BMD_ENG 220-0Introduction to Biomedical Statistics
CHEM_ENG 312-0Probability and Statistics for Chemical Engineering
CIV_ENV 306-0Uncertainty Analysis
IEMS 201-0Introduction to Statistics
IEMS 303-0Statistics
Course Title
​Programming Foundations (1 course)
COMP_SCI 150-0Fundamentals of Computer Programming 1.5
COMP_SCI 211-0Fundamentals of Computer Programming II
COMP_SCI 230-0Programming for Engineers
Course Title
Intermediate Programming/Algorithmic Skills (1 course)
COMP_SCI 214-0Data Structures & Algorithms
COMP_SCI 217-0Data Management & Information Processing
Course Title
Applied Machine Learning (1 course)
COMP_SCI 349-0Machine Learning
ELEC_ENG 375-0Machine Learning: Foundations, Applications, and Algorithms
IEMS 304-0Statistical Learning for Data Analysis

Data Science Studio Courses (2 units): 

Course Title
DATA_ENG 200-0Foundations of Data Science
DATA_ENG 300-0Data Engineering Studio

Elective Courses (2 units):

Course Title
BMD_ENG 311-0Computational Genomics
BMD_ENG 395-0Topics in Biomedical Engineering (Biomedical Applications in Machine Learning)
CHEM_ENG 379-0Computational Biology: Analysis and Design of Living Systems
CIV_ENV 304-0Civil and Environmental Engineering Systems Analysis
CIV_ENV 473-0Survey methods, data and analysis
CIV_ENV 480-1Travel Demand Analysis & Forecasting 1
CIV_ENV 480-2Advances in Travel Demand Analysis and Forecasting
CIV_ENV 495-0Selected Topics in Civil Engineering (Data Analytics for Transportation and Urban Infrastructure Applications)
COMP_SCI 348-0Introduction to Artificial Intelligence
COMP_SCI 394-0Agile Software Development
COMP_SCI 396-0Special Topics in Computer Science (Deep Learning) or (Interactive Information Visualization) or (Computing, Ethics, and Society) or (Visualization for Scientific Communication )
COMP_SCI 397-0Special Projects in Computer Science (Rapid Prototyping for Software Innovation)
ELEC_ENG 328-0Information Theory & Learning
ELEC_ENG 335-0Deep Learning Foundations from Scratch
ELEC_ENG 373-0Deep Reinforcement Learning
ELEC_ENG 395-0Special Topics in Electrical Engineering (Optimization Techniques for Machine Learning and Deep Learning)
ELEC_ENG 424-0Distributed Optimization
ELEC_ENG 433-0Statistical Pattern Recognition
ES_APPM 345-0Applied Linear Algebra
ES_APPM 375-1Quantitative Biology I: Experiments, Data, Models, and Analysis
ES_APPM 375-2Quantitative Biology II: Experiments, Data, Models, and Analysis
ES_APPM 472-0Introduction to the Analysis of RNA Sequencing Data
ES_APPM 479-0Data Driven Methods for Dynamical Systems
IEMS 307-0Quality Improvement by Experimental Design
IEMS 308-0Data Science and Analytics
IEMS 313-0Foundations of Optimization
IEMS 340-0Field Project Methods
IEMS 341-0Social Networks Analysis
IEMS 351-0Optimization Methods in Data Science
MAT_SCI 391-0Process Design
MECH_ENG 301-0Introduction to Robotics Laboratory
MECH_ENG 395-0Special Topics in Mechanical Engineering (Mechanistic Data Science)
MECH_ENG 441-0Engineering Optimization for Product Design and Manufacturing
MECH_ENG 469-0Machine Learning and Artificial Intelligence for Robotics
MECH_ENG 495-0Selected Topics in Mechanical Engg (Sensory Navigation and Machine Learning for Robotics)