Campuses:
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Twin Cities Campus
Data Science MinorComputer Science and Engineering Administration
College of Science and Engineering
Link to a list of faculty for this program.
Contact Information
Data Science Graduate Program, Department of Computer Science and Engineering, University of Minnesota, 4-192 Keller Hall, 200 Union Street S.E., Minneapolis, MN 55455 (612- 625-4002; fax: 612-625-0572).
Email:
datascience@umn.edu
Website: http://datascience.umn.edu
The Data Science Minor provides a strong foundation in the science of Big Data and its analysis by gathering together the knowledge, expertise, and educational assets in data collection and management, data analytics, scalable data-driven pattern discovery, and the fundamental concepts behind these methods. Students completing this program will learn the state-of-the-art methods for treating Big Data and be exposed to the cutting edge methods and theory forming the basis for the next generation of Big Data technology.
Program Delivery
Prerequisites for Admission
Currently enrolled in a University of Minnesota M.S. or Ph.D. program.
For an online application or for more information about graduate education admissions, see the
General Information section of this
website.
Program Requirements
Use of 4xxx courses towards program requirements is not permitted.
Courses must be taken at the University of Minnesota Twin Cities Campus and on the A/F grading scale. Transfer coursework will not be accepted. A 3.0 GPA must be maintained in the courses used for the Data Science minor.
All students must take one course from each of the three emphasis areas for a total of at least 9 credits. Doctoral students must take an additional electives course for at least 3 credits.
Algorithmics
Take 1 or more course(s) totaling 3 or more credit(s) from the following:
·
CSCI 5521 - Machine Learning Fundamentals
(3.0 cr)
·
CSCI 5523 - Introduction to Data Mining
(3.0 cr)
·
CSCI 5525 - Machine Learning: Analysis and Methods
(3.0 cr)
·
EE 8591 - Predictive Learning from Data
(3.0 cr)
·
PUBH 7475 - Statistical Learning and Data Mining
(3.0 cr)
Statistics
Take 1 or more course(s) totaling 3 or more credit(s) from the following:
·
STAT 5101 - Theory of Statistics I
(4.0 cr)
·
STAT 5102 - Theory of Statistics II
(4.0 cr)
·
STAT 5302 - Applied Regression Analysis
(4.0 cr)
·
STAT 5511 - Time Series Analysis
(3.0 cr)
·
STAT 5401 - Applied Multivariate Methods
(3.0 cr)
·
STAT 8051 - Advanced Regression Techniques: linear, nonlinear and nonparametric methods
(3.0 cr)
·
PUBH 7440 - Introduction to Bayesian Analysis
(3.0 cr)
Infrastructure and Large Scale Computing
Take 1 or more course(s) totaling 3 or more credit(s) from the following:
·
CSCI 5105 - Introduction to Distributed Systems
(3.0 cr)
·
CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming
(3.0 cr)
·
CSCI 5707 - Principles of Database Systems
(3.0 cr)
·
CSCI 8980 - Special Advanced Topics in Computer Science
(1.0-3.0 cr)
·
EE 5351 - Applied Parallel Programming
(3.0 cr)
Program Sub-plans
Students are required to complete one of the following sub-plans.
Students may not complete the program with more than one sub-plan.
Master's
The master's minor requires one course from each of the three emphasis areas for a total of 9 credits.
Doctoral
In addition to one course from each of the three emphasis areas, doctoral students take one elective course from the following to complete the 12-credit minimum.
Biochemistry Electives (6 Credits)
Students cannot use a course from the department housing their degree program as an elective.
Take 1 or more course(s) totaling 3 or more credit(s) from the following:
·
STAT 5101 - Theory of Statistics I
(4.0 cr)
·
STAT 5102 - Theory of Statistics II
(4.0 cr)
·
STAT 5302 - Applied Regression Analysis
(4.0 cr)
·
STAT 5511 - Time Series Analysis
(3.0 cr)
·
STAT 5401 - Applied Multivariate Methods
(3.0 cr)
·
STAT 8051 - Advanced Regression Techniques: linear, nonlinear and nonparametric methods
(3.0 cr)
·
PUBH 7440 - Introduction to Bayesian Analysis
(3.0 cr)
·
PUBH 8401 - Linear Models
(3.0 cr)
·
PUBH 8432 - Probability Models for Biostatistics
(3.0 cr)
·
PUBH 7405 - Biostatistical Inference I
(4.0 cr)
·
PUBH 7430 - Statistical Methods for Correlated Data
(3.0 cr)
·
PUBH 7460 - Advanced Statistical Computing
(3.0 cr)
·
PUBH 8442 - Bayesian Decision Theory and Data Analysis
(3.0 cr)
·
EE 5531 - Probability and Stochastic Processes
(3.0 cr)
·
EE 5571 - Statistical Learning and Inference
(3.0 cr)
·
CSCI 5521 - Machine Learning Fundamentals
(3.0 cr)
·
CSCI 5523 - Introduction to Data Mining
(3.0 cr)
·
CSCI 5525 - Machine Learning: Analysis and Methods
(3.0 cr)
·
EE 8591 - Predictive Learning from Data
(3.0 cr)
·
PUBH 7475 - Statistical Learning and Data Mining
(3.0 cr)
·
CSCI 5302 - Analysis of Numerical Algorithms
(3.0 cr)
·
CSCI 5304 - Computational Aspects of Matrix Theory
(3.0 cr)
·
CSCI 5511 - Artificial Intelligence I
(3.0 cr)
·
CSCI 5512 - Artificial Intelligence II
(3.0 cr)
·
CSCI 5609 - Visualization
(3.0 cr)
·
CSCI 8314 - Sparse Matrix Computations
(3.0 cr)
·
EE 5239 - Introduction to Nonlinear Optimization
(3.0 cr)
·
EE 5251 - Optimal Filtering and Estimation
(3.0 cr)
·
EE 5542 - Adaptive Digital Signal Processing
(3.0 cr)
·
EE 8551 - Multirate Signal Processing and Applications
(3.0 cr)
·
EE 5561 - Image Processing and Applications: From linear filters to artificial intelligence
(3.0 cr)
·
EE 5581 - Information Theory and Coding
(3.0 cr)
·
EE 5585 - Data Compression
(3.0 cr)
·
EE 8231 - Optimization Theory
(3.0 cr)
·
IE 5531 - Engineering Optimization I
(4.0 cr)
·
IE 8534 - Advanced Topics in Operations Research
(1.0-4.0 cr)
·
CSCI 5105 - Introduction to Distributed Systems
(3.0 cr)
·
CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming
(3.0 cr)
·
CSCI 5707 - Principles of Database Systems
(3.0 cr)
·
CSCI 8980 - Special Advanced Topics in Computer Science
(1.0-3.0 cr)
·
EE 5351 - Applied Parallel Programming
(3.0 cr)
·
CSCI 5211 - Data Communications and Computer Networks
(3.0 cr)
·
CSCI 5231 {Inactive}
(3.0 cr)
·
CSCI 5271 - Introduction to Computer Security
(3.0 cr)
·
CSCI 5708 - Architecture and Implementation of Database Management Systems
(3.0 cr)
·
CSCI 5715 - From GPS, Google Maps, and Uber to Spatial Data Science
(3.0 cr)
·
CSCI 5980 - Special Topics in Computer Science
(1.0-3.0 cr)
·
CSCI 8701 - Overview of Database Research
(3.0 cr)
·
CSCI 8715 - Spatial Data Science Research
(3.0 cr)
·
CSCI 8725 - Databases for Bioinformatics
(3.0 cr)
·
EE 5371 - Computer Systems Performance Measurement and Evaluation
(3.0 cr)
·
EE 5381 {Inactive}
(3.0 cr)
·
EE 5501 - Digital Communication
(3.0 cr)
·
EE 8367 - Parallel Computer Organization
(3.0 cr)
·
CSCI 8205 - Parallel Computer Organization
(3.0 cr)
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Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Fall Even Year |
Credits: | 3.0 [max 3.0] |
Typically offered: | Fall Even Year |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall & Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall, Spring & Summer |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall |
Credits: | 3.0 [max 3.0] |
Grading Basis: | A-F or Aud |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 4707/CSci 5707/INET 4707 |
Typically offered: | Every Fall |
Credits: | 1.0 -3.0 [max 27.0] |
Typically offered: | Every Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 8205/EE 8367 |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 8205/EE 8367 |
Typically offered: | Every Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall & Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall, Spring & Summer |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall |
Credits: | 3.0 [max 3.0] |
Grading Basis: | A-F or Aud |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 3.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Fall Even Year |
Credits: | 3.0 [max 3.0] |
Typically offered: | Fall Even Year |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 4511W/CSci 5511 |
Prerequisites: | [2041 or #], grad student |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 5512W/CSci 5512 |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Fall Even Year |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | AEM 5451/EE 5251 |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | EE 5561/EE 8541 |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Fall Even Year |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 1.0 -4.0 [max 8.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 4707/CSci 5707/INET 4707 |
Typically offered: | Every Fall |
Credits: | 1.0 -3.0 [max 27.0] |
Typically offered: | Every Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 4211/CSci 5211/INET 4002 |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Spring Even Year |
Credits: | 1.0 -3.0 [max 27.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | EE 5371/5863 |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 8205/EE 8367 |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 8205/EE 8367 |
Typically offered: | Every Spring |