Campuses:
Twin Cities Campus
Data Science MinorComputer Science and Engineering
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, 4192 Keller Hall, 200 Union Street S.E., Minneapolis, MN 55455 (612 6254002; fax: 6126250572).
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 datadriven pattern discovery, and the fundamental concepts behind these methods. Students completing this program will learn the stateoftheart 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  Introduction to Machine Learning
(3.0 cr)
·
CSCI 5523  Introduction to Data Mining
(3.0 cr)
·
CSCI 5525  Machine Learning
(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  Introduction to Statistical Learning
(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
(1.03.0 cr)
·
EE 5351  Applied Parallel Programming
(3.0 cr)
Program Subplans
Students are required to complete one of the following subplans.
Students may not complete the program with more than one subplan.
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 12credit 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  Introduction to Statistical Learning
(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
(4.0 cr)
·
PUBH 8432  Probability Models for Biostatistics
(3.0 cr)
·
PUBH 7405  Biostatistics: Regression
(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 8581  Detection and Estimation Theory
(3.0 cr)
·
CSCI 5521  Introduction to Machine Learning
(3.0 cr)
·
CSCI 5523  Introduction to Data Mining
(3.0 cr)
·
CSCI 5525  Machine Learning
(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 5551  Multiscale and Multirate Signal Processing
(3.0 cr)
·
EE 5561  Image Processing and Applications
(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
(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
(1.03.0 cr)
·
EE 5351  Applied Parallel Programming
(3.0 cr)
·
CSCI 5211  Data Communications and Computer Networks
(3.0 cr)
·
CSCI 5231  Wireless and Sensor Networks
(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 and Virtual Globes to Spatial Computing
(3.0 cr)
·
CSCI 5980  Special Topics in Computer Science
(1.03.0 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  Telecommunications Networks
(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)


Credits:  3.0 [max 3.0] 
Typically offered:  Periodic Fall 
Credits:  3.0 [max 3.0] 
Typically offered:  Periodic Fall & Spring 
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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] 
Course Equivalencies:  00260 
Typically offered:  Every Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall, Spring & Summer 
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Typically offered:  Every Fall 
Credits:  3.0 [max 3.0] 
Typically offered:  Periodic Fall 
Credits:  3.0 [max 3.0] 
Grading Basis:  AF 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 4707/5707/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] 
Course Equivalencies:  00260 
Typically offered:  Every 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:  AF or Aud 
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:  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:  01666 
Prerequisites:  [2041 or #], grad student 
Typically offered:  Every Fall 
Credits:  3.0 [max 3.0] 
Course Equivalencies:  CSci 5512W/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:  01703  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:  01244  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:  4.0 [max 8.0] 
Typically offered:  Every 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 4707/5707/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:  00495  CSci 4211/CSci 5211 
Typically offered:  Every Fall 
Credits:  3.0 [max 3.0] 
Typically offered:  Spring Odd Year 
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:  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 