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Ph.D.–Data Science Option

Doctor of Philosophy (Mechanical Engineering: Data Science): students will receive credentialed training in the analysis of large datasets. The goal of this option is to educate all students in the foundations of data science, so they may apply those methods and techniques in current research. The PhD Data Science is designed for students with little or no background in data science, computer science or coding.

The requirements for the Doctor of Philosophy (Mechanical Engineering: Data Science) are as follows:

I. Courses from three out of four of the following areas

1. Software development for data science

Recommended courses

Course #Course NameCredits
CSE 583Software Development for Data Scientists4
AMATH 583High Performance Scientific Computing5
ME 574Introduction to Applied Parallel Computing for Engineers3

2. Statistics and machine learning

Recommended courses

Course #Course NameCredits
CSE416/STAT416Introduction to Machine learning4
AMATH 582Computational Methods for Data Analysis5
AMATH 563Inferring Structure of Complex Systems5
AMATH 515Fundamentals of Optimization5
ME/EE 578Convex Optimization4
ME 599Machine Learning Control3
CSE 599UReinforcement Learning4
STAT 527Nonparametric regression and classification3
CSE 546/STAT 535Machine Learning
also serves for the “Advanced Data Science Option”
4/3
STAT 509Introduction to Mathematical Statistics
also serves for the “Advanced Data Science Option”
4
STAT 512-513Statistical Inference
also serves for the “Advanced Data Science Option”
4
ME 599Data-Driven Modeling of Dynamical Systems (Manohar)3
CSE/AMATH 579Intelligent Control Through Learning and Optimization3
ME 599Introduction of AI for Clean Energy3

3. Data management and data visualization

Recommended Courses

Course #Course NameCredits
CSE 414Introduction to Database Systems4
CSE 412Introduction to Data Visualization4
HCDE 411/511Information for Visualization4
BIOEN 420Medical Imaging4
BIOEN 451/551Optical Coherence Tomography4
BIOEN 546Fundamentals of Biomedical Imaging4
CSE 544Principles of DBMS
also serves for the “Advanced Data Science Option”
4
CSE 512Data Visualization
also serves for the “Advanced Data Science Option”
4

4. Department specific requirement

If listed above, then course doesn’t count twice

Recommended courses

Course #Course NameCredits
CSE 455Computer Vision4
EE/CSE 576Computer Vision3
ME/EE 578Convex Optimization4
ME 599Machine Learning Control3
ME 574Introduction to Applied Parallel Computing for Engineers3
CSE/AMATH 579Intelligent Control Through Learning and Optimization3

II. eScience Community Seminar

  • 2 quarters of the eScience Community Seminar, ENGR 591-Data Science Seminar, or ME 520- Data Drive seminar with Professor Steve Brunton. Seminar credits do not count towards graduation requirements. 

III. Fulfillment of the Mechanical Engineering requirements

In addition, all students are required to take at least one additional course in quantitative methods (statistics, applied mathematics, mathematics, or computational science) OR in a methodology directly relevant to their area of focus. Such courses are to be specified in each student’s Individualized Training Plan.
Course #Course NameCredits
CSE416/STAT416Introduction to Machine Learning4
STAT 527Nonparametric Regression and Classification3
STAT 535Statistical Learning: Modeling, Prediction, and Computing3
STAT 509Econometrics I: Introduction to Mathematical Statistics4
STAT 512/513Statistical Inference4
ME/EE 578Convex Optimization4
ME 599Machine Learning Control3
ME 599Data-Driven Modeling of Dynamical Systems (Manohar)3
Amath 515Optimization: Fundamentals and Applications5
Amath 563Inferring Structure of Complex Systems5
Amath 582Computational Methods for Data Analysis5
Amath 583High-Performance Scientific Computing5

Students may not count any course toward both the ME coursework requirements and the Data Science requirements. For example, if students take ME 574 and count it toward the computational or numerical analysis requirement, they cannot use this course to fulfill the Data Science requirement. Students must ensure that there’s a minimum of 9 distinct credits taken for the Data science option.