What is the UW-Madison MS-Data Engineering Degree?
Data engineers ensure that increasing amounts of data being generated and processed on a daily basis are usable by the time they reach data scientists and analysts. This program prepares students for employment in this exponentially growing field.
Who is the program for?
This program is for anyone with a background in computer science who wants to pursue a career in data engineering. If you're interested in making high-quality data accessible to scientists and analysts, this degree is for you.
Questions? Need more information? Email us!
Admissions
This is an accordion element with a series of buttons that open and close related content panels.
Dates and to apply
Fall admissions only:
- 2022 deadline: July 15
- 2023 deadline: March 15
Application materials and requirements
Applicants to the program should have completed a bachelor’s degree in computer science or a related field.
GRE not required.
Three letters of recommendation required.
English proficiency if your native language is not English: See requirements on the Graduate School Application Page.
Curricular Requirements
Minimum Credit Requirement
30 credits
Minimum Residence Credit Requirement
16 credits
Minimum Graduate Coursework Requirement
15 credits must be graduate-level coursework
Details can be found in the Graduate School’s Minimum Graduate Coursework (50%) policy .
Overall Graduate GPA Requirement
3.00 GPA required
This program follows the Graduate School’s policy.
Sample Curriculum: 30 credits required
This is an accordion element with a series of buttons that open and close related content panels.
Data Engineering Foundations - complete all classes
COMP SCI 739
Distributed Systems
COMP SCI 744
Big Data Systems
COMP SCI 764
Topics in Database Management Systems
COMP SCI 838
Topics in Computing 1
Machine Learning - select a minimum of two courses
COMP SCI 540
Introduction to Artificial Intelligence
COMP SCI/E C E 760
Machine Learning
COMP SCI 762
Advanced Deep Learning
STAT 451
Introduction to Machine Learning and Statistical Pattern Classification
STAT 453
Introduction to Deep Learning and Generative Models
STAT 615
Statistical Learning
Algorithms Requirement - select a minimum of 1 course
COMP SCI/E C E/I SY E 524
Introduction to Optimization
COMP SCI 577
Introduction to Algorithms
COMP SCI/I SY E/MATH/STAT 726
Nonlinear Optimization I
Systems Requirement - select a minimum of one course
COMP SCI 407
Foundations of Mobile Systems and Applications
COMP SCI 537
Introduction to Operating Systems
COMP SCI 564
Database Management Systems: Design and Implementation
COMP SCI 640
Introduction to Computer Networks
COMP SCI/E C E 707
Mobile and Wireless Networking
COMP SCI 740
Advanced Computer Networks
Humans and Data Requirement: select a minimum of one course
COMP SCI 765
Data Visualization
COMP SCI/ED PSYCH/PSYCH 770
Human-Computer Interaction
Approved Electives: select any course from above or from the list below
COMP SCI 642
Introduction to Information Security
COMP SCI 702
Graduate Cooperative Education 2
COMP SCI 790
Master’s Thesis 2
COMP SCI 799
Master’s Research 2
COMP SCI 900
Advanced Seminar in Computer Science 2
STAT 611
Statistical Models for Data Science
STAT 612
Statistical Inference for Data Science
STAT 613
Statistical Methods for Data Science
