DATA SCIENCE, MS

Computer Science

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Requirements		Hours
Select 24 credit hours of CS courses and approved non-CS electives at the 500+ level 1,2		24
Allowed Electives from other disciplines (up to 3 chrs)
MA 660	Numerical Linear Algebra 3
MA 668	Numerical Analysis I 3
or
MA 669	Numerical Analysis II 3
CS 699	Master's Thesis Research	6
Total Hours		30

Requirements		Hours
Select 30 credit hours of CS courses and approved non-CS electives at the 500+ level 1,2		30
Allowed Electives from other disciplines (up to 3 chrs)
MA 660	Numerical Linear Algebra 3
MA 668	Numerical Analysis I 3
or
MA 669	Numerical Analysis II 3
Total Hours		30

1	No more than three (9 credit hours of) 500 level courses can count towards the MS degree
2	No more than one (3 credit hours of) special course (CS 697 or CS 598) can count towards the MS degree
3	May substitute any other graduate level course approved by the graduate program director

Requirements		Hours
Core		12
CS 510	Database Application Development
or CS 610	Database Systems
CS 652	Advanced Algorithms and Applications
CS 667	Machine Learning
CS 685	Foundations of Data Science
or CS 680	Matrix Algorithms for Data Science
Electives 1		12
Data Analytics
CS 616	Big Data Programming
CS 660	Artificial Intelligence
CS 662	Natural Language Processing
CS 663	Data Mining
CS 665	Deep Learning
CS 673	Computer Vision and Convolutional Neural Networks
CS 675	Data Visualization
CS 680	Matrix Algorithms for Data Science
CS 687	Complex Networks
Cyber Security
CS 636	Computer Security
CS 623	Network Security
CS 645	Modern Cryptography
CS 643	Cloud Security
High Performance Computing
CS 632	Parallel Computing
CS 633	Cloud Computing
Digital Forensics
CS 519	Investigating Online Crimes
CS 537	Digital Media Forensics
CS 689	Cyber Risk Management
Non-Computer Science Electives 2
Biostatistics
BST 611	Intermediate Statistical Analysis I
BST 612	Intermediate Statistical Analysis II
BST 621	Statistical Methods I
BST 622	Statistical Methods II
Bioinformatics
INFO 601	Introduction to Bioinformatics
INFO 602	Algorithms in Bioinformatics
INFO 603	Biological Data Management
Business Intelligence
MBA 617	Data Science for Business
MBA 658	Applied Marketing Research
MBA 662	Quantitative Analysis for Business Managers
Thesis Research		6
CS 699	Master's Thesis Research
Total Hours		30

Requirements		Hours
Core		12
CS 510	Database Application Development
or CS 610	Database Systems
CS 652	Advanced Algorithms and Applications
CS 667	Machine Learning
CS 685	Foundations of Data Science
or CS 680	Matrix Algorithms for Data Science
Electives 1		18
Data Analytics
CS 616	Big Data Programming
CS 660	Artificial Intelligence
CS 662	Natural Language Processing
CS 663	Data Mining
CS 665	Deep Learning
CS 673	Computer Vision and Convolutional Neural Networks
CS 675	Data Visualization
CS 680	Matrix Algorithms for Data Science
CS 687	Complex Networks
Cyber Security
CS 636	Computer Security
CS 623	Network Security
CS 645	Modern Cryptography
CS 643	Cloud Security
High Performance Computing
CS 632	Parallel Computing
CS 633	Cloud Computing
Digital Forensics
CS 519	Investigating Online Crimes
CS 537	Digital Media Forensics
CS 689	Cyber Risk Management
Non-Computer Science Electives 2
Biostatistics
BST 611	Intermediate Statistical Analysis I
BST 612	Intermediate Statistical Analysis II
BST 621	Statistical Methods I
BST 622	Statistical Methods II
Bioinformatics
INFO 601	Introduction to Bioinformatics
INFO 602	Algorithms in Bioinformatics
INFO 603	Biological Data Management
Business Intelligence
MBA 617	Data Science for Business
MBA 658	Applied Marketing Research
MBA 662	Quantitative Analysis for Business Managers
Total Hours		30

1	At most three credit hours of special courses (CS 697: Directed Readings or CS 598: Practical Work Experience) can count towards the MSDS degree. No more than three (9 credit hours of) 500 level courses can count towards the MSDS degree.
2	Students may take up to three (9 credit hours of) non-CS electives upon the approval of the graduate program director.