About the Program
The Designated Emphasis (DE) in Computational and Data Science and Engineering Program (CDSE) at the University of California, Berkeley trains students in modeling and high-performance simulation of complex physical systems, as well as in several aspects of data analysis, statistics, machine learning, data visualization, etc. The CDSE program is committed to the development of new curricula and expanded programs aimed at the development and propagation of the use of tools of scientific computation to enhance research across multiple disciplines. To that end, the CDSE program will actively support the training and multidisciplinary education of scientists, engineers, and technical specialists who are experts in relevant areas.
The CDSE program crosses numerous disciplines, and participating departments include all of the departments in the college of engineering, computer science, mathematics, chemistry, astronomy, neuroscience, and political science, among many others.
Upon graduation, the student receives a “PhD in X with a Designated Emphasis in Computational and Data Science and Engineering” on their transcript and diploma. This designation certifies that she or he has successfully completed a designated emphasis in addition to the departmental requirements for the PhD. Completion of the DE-CDSE will also be posted to the student’s transcript. We encourage interested readers to visit data.berkeley.edu/decdse.
Admissions
Applicants must already be students within a Ph.D. program at UC Berkeley.
Students must be accepted into the program and petition to add the DE-CDSE before taking their Qualifying Exam.
Applicants for the DE-CDSE program are required to:
- Submit an online application; for access to the application, please see the program's website.
- With this form, the student must specify their proposed area of CDSE study and list which three courses they will take to fulfill the requirements.
- Curriculum Vitae (CV)
- Transcripts (most recent copy of all undergraduate and graduate transcripts)
- Letter of recommendation from their advisor
- One-page statement about why they are applying to the program
For further information regarding admission to graduate programs at UC Berkeley, please see the Graduate Division's Admissions website.
Designated Emphasis Requirements
Coursework/Curriculum
The student must take one course from each of the categories below; all courses taken to fulfill the DE requirements must be taken for a letter grade.
| Code | Title | Units |
|---|---|---|
| Category 1: Mathematical Tools | ||
| Select one of the following: | ||
| Advanced Matrix Computations [4] | ||
| Numerical Solution of Differential Equations [4] | ||
| Numerical Solution of Differential Equations [4] | ||
| Probability for Applications [4] | ||
| Theoretical Statistics [4] | ||
| Theoretical Statistics [4] | ||
| Applied Statistics and Machine Learning [4] | ||
| Statistical Models: Theory and Application [4] | ||
| Experimental Design [4] | ||
| The Statistics of Causal Inference in the Social Science [4] | ||
| Nonparametric and Robust Methods [4] | ||
| Statistical Learning Theory [3] | ||
| Advanced Topics in Learning and Decision Making [3] | ||
| Introduction to Statistical Computing [4] | ||
| Computing for Statistics and Data Science with Julia,Statistical Computing [2,4] | ||
| Analysis of Time Series [4] | ||
A course not listed, by petition to the program director | ||
| Category 2: High Performance Computing | ||
| Select one of the following: | ||
| COMPSCI C267 | Applications of Parallel Computers | 3-4 |
| COMPSCI 286A | Introduction to Database Systems | 4 |
| COMPSCI 289A | Introduction to Machine Learning | 4 |
| COMPSCI 294 | Special Topics | 1-4 |
| CS 294-73 "Software Engineering for Scientific Computing" | ||
| CS 294-127 "Computational Imaging" | ||
| CS 297-143 "Design, Evaluation, and Implementation of Modern Warehouse-Scale Computers" | ||
| STAT 259 | Reproducible and Collaborative Statistical Data Science | 4 |
| CHEM/BIO ENG C242 | Machine Learning, Statistical Models, and Optimization for Molecular Problems | 4 |
| Category 3: Application area | ||
| Application area courses that utilize the above tools in a significant manner 1 | ||
- 1
The student proposes this course, including a detailed syllabus documenting the use of mathematics and computation in an application area.
Qualifying Exam
Students must have a DE-CDSE component in their qualifying exam, with a DE-CDSE faculty member on the exam committee.
Dissertation
At least one member of the DE-CDSE faculty be on the dissertation committee.
Contact Information
Computational and Data Science and Engineering
Department Chair
Tarek I. Zohdi, PhD (Department of Mechanical Engineering)
Phone: 510-642-9172
Head Graduate Advisor
Michael Frenklach, PhD (Department of Mechanical Engineering)
Phone: 510-643-1676