Data Science

The Data Science master's degree program is designed as a 30-credit hour interdisciplinary graduate program. The curriculum consists of required core courses and technical electives, providing opportunities to build knowledge and professional skills in various Data Science areas that are highly demanded in the current job market. This program can be completed fully online, in person, or a combination of both. Four specializations are recommended (not mandatory) for students with different interests in Data Science:

Computational Intelligence Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to solve complex data analytics problems through learning and adapting based on data.

Applications Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to develop effective data analytics solutions in selected application domains. 

Business Analytics Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to apply intelligent strategies and technologies to support the collection, data analysis, presentation and dissemination of business information in enterprises. 

Big Data Informatics Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to apply cutting-edge technologies and tools to tackle Big Data challenges that are essential for data processing and analytics in numerous applications. 

Degree Requirements

Regular admission to the program requires a Bachelor degree in a Science, Technology, Engineering, or Mathematics (STEM) field earned from an accredited program with an average of B or better. Each applicant is required to present official, complete transcripts of prior college work. Two letters of recommendation are required for admission. At least one letter must be from someone familiar with the candidate's academic performance. An entering student should have completed one course in probability and statistics, one course in programming, and one course in calculus II. A course in calculus III and a course in linear algebra are recommended but not required. 

To satisfy the requirements for the MS degree in Data Science, all students admitted to the program are expected to complete 30 credit hours of approved graduate coursework, with a cumulative grade point average of B or better. 

1Please contact the Computer and Information Science Department about the policy on the minimum grade for a course to satisfy graduation requirements

Requirements 

Core Courses (18 credit hours)

Required
CIS/IMSE 556Database Systems3
Choose one course (3 credit hours) from:
CIS 5570Introduction to Big Data3
IMSE 586Big Data Aanal & Visuliztn3
Choose one course (3 credit hours) from:
ECE 537/CIS 568Data Mining3
ECE 579Intelligent Systems3
DS 633Data Mining for Business Appl3
Choose one course (3 credit hours) from:
IMSE 514Multivariate Statistics3
STAT 530Applied Regression Analysis3
STAT 535Data Analysis and Modeling3
STAT 560Time Series Analysis3
Choose one course (3 credit hours) from:
DS 570Management Science3
IMSE 500Models of Oper Research3
Choose one course (3 credit hours) from:
CIS 545Data Security and Privacy3
ECE 527Multimedia Secur & Forensics3
HHS 570Information Science and Ethics3

Specialization Courses (9 credit hours)

Note that the specializations are offered for guidance only. Students may select three courses from one specialization or three courses from multiple specializations for a broader approach to the degree. For students who are interested in selecting the Business Analytics Specialization, they need to choose 3 courses in that specialization as specified. 

One of the following specializations is recommended:

Computational Intelligence Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to solve complex data analytics problems through learning and adapting based on data.

CIS 511Natural Language Processing3
CIS 555Decision Support and Expert Systems3
CIS 5700Advanced Data Mining3
CIS 579Artificial Intelligence3
CIS 581Computational Learning3
CIS 585Advanced Artificial Intelligence3
CIS 685Research Advances in Artificial Intelligence3
ECE 537/CIS 568Data Mining3
ECE 552Fuzzy Systems3
ECE 555Stochastic Processes3
ECE 579Intelligent Systems3
ECE 5831Pat Rec & Neural Netwks3
ECE 679Adv Intelligent Sys3
IMSE 505Optimization3
IMSE 5205Eng Risk-Benefit Analysis3
IMSE 559System Simulation3
IMSE 605Advanced Optimization3
MATH 520Stochastic Processes3
MATH 562Mathematical Modeling3
MATH 573Matrix Computation3
STAT 530Applied Regression Analysis3
STAT 545Reliability & Survival Analys3
STAT 560Time Series Analysis3

Applications Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to develop effective data analytics solutions in selected application domains. 

CIS 580Data Analytics in Software Engineering3
ESCI 585Spatial Analysis and GIS3
FIN 531Fin Fundament & Value Creation3
HIT 520Clinical & Evidence Based Med3
IMSE 516Project Management and Control3
IMSE 561Tot Qual Mgmt and Six Sigma3
IMSE 5655Supply Chain Management3
IMSE 567Reliability Analysis3
IMSE 580Prod & Oper Engineering I3
MKT 515Marketing Management3
OM 521Operations Management3
OM 571Supply Chain Management3
STAT 545Reliability & Survival Analys3
STAT 560Time Series Analysis3

Business Analytics Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to apply intelligent strategies and technologies to support the collection, data analysis, presentation and dissemination of business information in enterprises. 

Choose two courses from:
DS 630Applied Forecasting3
DS 631Decision Analysis3
DS 632System Simulation3
Choose one course from:
FIN 531Fin Fundament & Value Creation3
MIS 525Computer and Info Systems3
MKT 515Marketing Management3
OM 521Operations Management3

Big Data Informatics Specialization

This specialization is recommended for those students who are interested in building their knowledge and professional skills to apply cutting-edge technologies and tools to tackle Big Data challenges that are essential for data processing and analytics in numerous applications. 

CIS 511Natural Language Processing3
CIS 515Computer Graphics3
CIS 534Semantic Web3
CIS 536Text Mining and Information Retrieval3
CIS 540Foundation of Information Security3
CIS 548Security and Privacy in Cloud Computing3
CIS 552Information Visualization and Virtualization3
CIS 554Info Sys Analysis and Design3
CIS 559Principles of Social Network Science3
CIS 560Electronic Commerce3
CIS 562Web Information Management3
CIS 5570Introduction to Big Data3
CIS 5700Advanced Data Mining3
CIS 571Web Services3
CIS 577S/W User Interface Dsgn&Analys3
CIS 586Advanced Data Management3
CIS 590JSelected Topic: Edge Computing3
CIS 590KSelected Topic: Deep Learning3
CIS 652Advanced Information Visualization and Virtualization3
CIS 658Research Advances in Data Management3
ECE 524Interactive Media3
ECE 525Multimedia Data Stor & Retr3
ECE 5251MM Design Tools I3
ECE 5252MM Design Tools II3
ECE 528Cloud Computing3
ECE 576Information Engineering3
ESCI 585Spatial Analysis and GIS3
IMSE 570Enterprise Information Systems3
IMSE 577Human-Computer Interaction3
IMSE 586Big Data Aanal & Visuliztn3
OM 665IT in SCM3

Coursework/Capstone/Thesis (3 credit hours)

Students in this program should choose one of three options: (1) coursework, (2) capstone project, or (3) thesis.

Option 1: Coursework. Students choosing this option must take one additional course (3 credit hours) from a specialization area listed above.

Option 2: Capstone Project. Students choosing this option must complete a capstone project under the supervision of a faculty advisor through a capstone course (3 credit hours). Acceptable capstone courses are:

CIS 695Master's Project3
DS 635Analytics Experience Capstone3
ECE 695Master's Project3
EMGT 590Capstone Project3

Option 3: Thesis. Students choosing this option must complete a thesis under the supervision of a faculty advisor through a thesis course (6 credit hours). Acceptable thesis courses are: CIS 699, IMSE 699, and ECE 699. Students only need to take two (instead of three) specialization courses (6 credit hours) in this option.

Note that no more than a total of 15 credit hours may be taken in the College of Business for this degree (core, specializations, and capstone/thesis).