Overview
Data science plays a major role in many areas of computational science and engineering (CSE). The Data Science & Engineering (DSE) Transcriptable Graduate Concentration is designed for graduate students at the Ph.D. levels with an interest in data-intensive computing.
This concentration requires students to complete 16 graduate credit hours spanning data science, from topics in mathematical foundations (MF), computational thinking (CT), statistical thinking (ST), as well as data management, description, and modeling (DX). Courses taken toward this concentration will count towards the student’s graduate degree if permitted by the curriculum of their major, and the concentration will be listed on their transcript upon graduation. To fulfill the requirements of the graduate concentration, students will take courses selected from an established list of core courses, along with courses from a selection of elective courses that span a range of domain areas. Students may select any course in the list of electives, regardless of their enrolled degree program. The DSE concentration also requires satisfactory completion of an online course and one seminar on data science, ethics, and social justice.
Eligibility
The DSE graduate concentration is available for students enrolled in participating graduate degree programs:
- Aerospace Engineering, PhD
- Agricultural & Biological Engineering, PhD
- Bioengineering, PhD
- Civil Engineering, PhD
- Computer Science, PhD
- Electrical & Computer Engineering, PhD
- Industrial Engineering, PhD
- Materials Science & Engineering, PhD
- Mechanical Engineering, PhD
- Nuclear, Plasma, & Radiological Engineering, PhD
- Physics, PhD
- Statistics, PhD
Enrollment Procedure
We are now accepting applications for Fall 2023 admission. The deadline is October 13, 2023. Due to limited resources, we may not accept all applications. Preference will be given to early applications determined by the application date.
Please submit the DSE Concentration Application Form.
Requirements
Core Coursework |
8 | |
| Select at least one course from two of the three groups below. | ||
| Mathematical Foundations (MF) &Statistical Thinking (ST) | ||
| Statistical Modeling I | ||
| Basics of Statistical Learning | ||
| Advanced Data Analysis | ||
| Applied Machine Learning | ||
| Machine Learning | ||
| Mathematical Foundations (MF) & Computational Thinking (CT) | ||
| Numerical Analysis | ||
| Parallel Programming | ||
| Statistical Computing * | ||
| Data Description and Curation (DX) & Data Modeling (DX) | ||
| Data Science Foundations | ||
| Introduction to Data Mining | ||
| Total Hours | 16 | |
Approved Elective Courses
| Complete two additional courses from the approved list. | |
| General Electives | |
| Applied Stochastic Processes | |
| Statistical Learning | |
| Uncertainty Quantification | |
| Advanced Data Management | |
| Data Visualization | |
| Uncertainty Quantification | |
| Mechanical Science and Engineering | |
| Mfg Data and Quality Systems | |
| Experimental Fluid Mechanics | |
| Turbulence | |
| Atomistic Solid Mechanics | |
| Civil and Environmental Engineering | |
| Globalization of Water | |
| Stochastic Hydrology | |
| Geotechnical Field Measurement | |
| Construction Data Modeling | |
| Structural Dynamics II | |
| Materials | |
| Intro to Digital Materials | |
|
ME 498 (ME 453)
|
Mfg Data and Quality Systems |
| Additive Manufacturing and Product Design | |
| Industrial & Enterprise Systems Engineering | |
| Algorithms for Data Analytics | |
| Optimization Methods for Large Scale Networks | |
| Physics | |
| Statistical Data Analysis and Stochastic Processes in Physics | |
| Bioengineering | |
| Computational Bioengineering | |
| Applied Deep Learning for Biomedical Imaging | |
* MATH 564 | STAT 555 is the correct course (instead of MATH 555 as shown in an earlier version) in this category. If you have any questions, please contact Bryan Wang (bpcwang@illinois.edu).
Other Requirements
| At least 4 hours of coursework for the DSE concentration should be advanced (500-level courses) |
| For students enrolled in both the DSE concentration and the CSE concentration, at least 12 hours of coursework earned for the DSE concentration must be distinct from credit earned for the CSE concentration. |
Suggest a DSE course (faculty/staff only)
FAQ
Q: What is a concentration?
A: A graduate concentration constitutes a coherent program of study requiring additional breadth or considerable depth of knowledge. A concentration may refer to a subfield within a discipline, or to an interdepartmental and/or interdisciplinary area of knowledge. Concentrations appear on academic transcripts.
Q: I’m not a current student at the University of Illinois at Urbana-Champaign, can I directly apply for DSE?
A: Only current students in the participating degree programs are eligible for the DSE graduate concentration. You can check the websites of the degree programs and contact them directly for any questions about the application process.
Q: I’m a doctoral student in a department that is not on the list, can I enroll in the DSE graduate concentration?
A: The DSE graduate concentration is only available for students enrolled in participating graduate degree programs.
Q: I’m in a Master’s program in the participating departments, can I enroll in the DSE graduate concentration?
A: The DSE graduate concentration is only available for students enrolled in participating graduate degree programs. They are all at the Ph.D. level.
Q: I have earned some credits on the approved list before application. Do they count?
A: Yes. The credits you have earned during your current program will count.
Q: Do I need to pay for additional tuition or fees for the DSE concentration?
A: There is no additional tuition or fees.
Q: I have other questions, who should I contact?
A: Please contact CSE education coordinator Bryan Wang bpcwang@illinois.edu