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 minor 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
Special Application Requirements:
Students interested in the minor are strongly encouraged to confer with their major field advisor and director of graduate studies, and the Data Science director of graduate studies regarding feasibility and requirements.
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; transfer coursework will not be accepted.
Courses must be taken on the A/F grading scale.
A 3.0 GPA must be maintained in the courses applied to the Data Science minor.
Algorithmics (3 credits)
All students select 3 credits 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 (3 credits)
All students select 3 credits from the following:
PUBH 7401 - Fundamentals of Biostatistical Inference
(4.0 cr)
PUBH 7402 - Biostatistics Modeling and Methods
(4.0 cr)
PUBH 7440 - Introduction to Bayesian Analysis
(3.0 cr)
STAT 5102 - Theory of Statistics II
(4.0 cr)
STAT 5302 - Applied Regression Analysis
(4.0 cr)
STAT 5401 - Applied Multivariate Methods
(3.0 cr)
STAT 5511 - Time Series Analysis
(3.0 cr)
STAT 8051 - Advanced Regression Techniques: linear, nonlinear and nonparametric methods
(3.0 cr)
Infrastructure and Large Scale Computing (3 credits)
All students select 3 credits 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.
Masters
Doctoral
Coursework from the student's home department cannot be applied as a doctoral minor elective.
Electives (3 Credits)
Select 3 credits from the following to complete the 12-credit minimum for the doctoral minor.
CSCI 5105 - Introduction to Distributed Systems
(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 5302 - Analysis of Numerical Algorithms
(3.0 cr)
CSCI 5304 - Computational Aspects of Matrix Theory
(3.0 cr)
CSCI 5451 - Introduction to Parallel Computing: Architectures, Algorithms, and Programming
(3.0 cr)
CSCI 5511 - Artificial Intelligence I
(3.0 cr)
CSCI 5512 - Artificial Intelligence II
(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)
CSCI 5609 - Visualization
(3.0 cr)
CSCI 5707 - Principles of Database Systems
(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 5801 - Software Engineering I
(3.0 cr)
CSCI 5802 - Software Engineering II
(3.0 cr)
CSCI 5980 - Special Topics in Computer Science
(1.0-3.0 cr)
CSCI 8102 - Foundations of Distributed Computing
(3.0 cr)
CSCI 8205 - Parallel Computer Organization
(3.0 cr)
CSCI 8314 - Sparse Matrix Computations
(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)
CSCI 8735 - Advanced Database Systems
(3.0 cr)
CSCI 8801 - Advanced Software Engineering
(3.0 cr)
CSCI 8980 - Special Advanced Topics in Computer Science
(1.0-3.0 cr)
EE 5239 - Introduction to Nonlinear Optimization
(3.0 cr)
EE 5251 - Optimal Filtering and Estimation
(3.0 cr)
EE 5351 - Applied Parallel Programming
(3.0 cr)
EE 5355 - Algorithmic Techniques for Scalable Many-core Computing
(3.0 cr)
EE 5371 - Computer Systems Performance Measurement and Evaluation
(3.0 cr)
EE 5381 {Inactive}
(3.0 cr)
EE 5391 {Inactive}
(3.0 cr)
EE 5501 - Digital Communication
(3.0 cr)
EE 5531 - Probability and Stochastic Processes
(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)
EE 8367 - Parallel Computer Organization
(3.0 cr)
EE 5571 - Statistical Learning and Inference
(3.0 cr)
EE 8591 - Predictive Learning from Data
(3.0 cr)
IE 5531 - Engineering Optimization I
(4.0 cr)
IE 8521 - Optimization
(4.0 cr)
IE 8531 - Discrete Optimization
(4.0 cr)
IE 8534 - Advanced Topics in Operations Research
(1.0-4.0 cr)
PUBH 7401 - Fundamentals of Biostatistical Inference
(4.0 cr)
PUBH 7402 - Biostatistics Modeling and Methods
(4.0 cr)
PUBH 7405 - Biostatistical Inference I
(4.0 cr)
PUBH 7406 - Biostatistical Inference II
(3.0 cr)
PUBH 7407 - Analysis of Categorical Data
(3.0 cr)
PUBH 7430 - Statistical Methods for Correlated Data
(3.0 cr)
PUBH 7440 - Introduction to Bayesian Analysis
(3.0 cr)
PUBH 7460 - Advanced Statistical Computing
(3.0 cr)
PUBH 7475 - Statistical Learning and Data Mining
(3.0 cr)
PUBH 7485 - Methods for Causal Inference
(3.0 cr)
PUBH 8401 - Linear Models
(3.0 cr)
PUBH 8432 - Probability Models for Biostatistics
(3.0 cr)
PUBH 8442 - Bayesian Decision Theory and Data Analysis
(3.0 cr)
STAT 5101 - Theory of Statistics I
(4.0 cr)
STAT 5102 - Theory of Statistics II
(4.0 cr)
STAT 5201 - Sampling Methodology in Finite Populations
(3.0 cr)
STAT 5302 - Applied Regression Analysis
(4.0 cr)
STAT 5303 - Designing Experiments
(4.0 cr)
STAT 5401 - Applied Multivariate Methods
(3.0 cr)
STAT 5421 - Analysis of Categorical Data
(3.0 cr)
STAT 5511 - Time Series Analysis
(3.0 cr)
STAT 5601 - Nonparametric Methods
(3.0 cr)
STAT 8051 - Advanced Regression Techniques: linear, nonlinear and nonparametric methods
(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 Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
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: | Periodic Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Grading Basis: | A-F or Aud |
Typically offered: | Every Fall |
Credits: | 4.0 [max 4.0] |
Course Equivalencies: | Math 5651/Stat 5101 |
Typically offered: | Every Fall & Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
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: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
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: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
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: | 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] |
Course Equivalencies: | CSci 4707/CSci 5707/INET 4707 |
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: | 3.0 [max 3.0] |
Prerequisites: | 2041 or # |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 1.0 -3.0 [max 27.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 8205/EE 8367 |
Typically offered: | Every Spring |
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] |
Typically offered: | Periodic Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Grading Basis: | A-F or Aud |
Typically offered: | Periodic Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 1.0 -3.0 [max 27.0] |
Typically offered: | Every Fall & 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: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Spring Odd Year |
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] |
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: | 3.0 [max 3.0] |
Course Equivalencies: | CSci 8205/EE 8367 |
Typically offered: | Every Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Fall Even Year |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 4.0 [max 8.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 1.0 -4.0 [max 8.0] |
Typically offered: | Periodic Fall & Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 4.0] |
Typically offered: | Every 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] |
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: | Every Fall |
Credits: | 3.0 [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 Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Spring |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall, Spring & Summer |
Credits: | 4.0 [max 4.0] |
Typically offered: | Every Fall, Spring & Summer |
Credits: | 3.0 [max 3.0] |
Typically offered: | Periodic Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall & Spring |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall |
Credits: | 3.0 [max 3.0] |
Typically offered: | Every Fall & Spring |
Credits: | 3.0 [max 3.0] |
Grading Basis: | A-F or Aud |
Typically offered: | Every Fall |