M.S. in Data Science

Students will:

  • Apply data mining and database knowledge to identify, retrieve, cleanse and store data.
  • Apply their learning from project-based coursework to solve new unknown problems.
  • Apply knowledge of statistical inference and machine learning tools to real industry applications obtained by methods including, but not limited to, case studies or detailed literature reviews.

Degree Requirements

The curriculum consists of 15 credits of required coursework, with an additional 3 credits of track-specific required course and 12 credits of electives and/or thesis research.

The core courses provide the foundation of the Data Science principles and require an undergraduate degree in a technical field (a degree with at least four semesters of college-level Math) for preparation. Students with a non-technical undergraduate degree will be required to complete additional modules

Program Core
CS 540Database and Information Retrieval3
DS 540Data Mining3
DS 544Data Visualization3
DS 615Data Modeling3
MA 506Probability and Statistical Inference3
Total Credits15

Aerospace Engineering Track

Required Courses
AE 514Introduction to the Finite Element Method3
AE 516Computational Aeronautical Fluid Dynamics3
AE 523Linear Systems3
Select one of the following3
AE 5XX Aerospace Engineering Elective
Numerical Methods for Engineers and Scientists
Numerical Linear Algebra for Engineers
Total Credits12

Aviation Business Track

Electives - Select 12 hours from the following:12
Accounting for Decision Making
Operations Research
Advanced Aviation Economics
Airline Optimization and Simulation Systems
Data Analytics for Aviation Business
Airport Operations and Management
Managerial Finance
International Aviation Finance
Aircraft Funding Legal and Financial Analysis
Total Credits12

 Aviation Safety Track

Electives - Select 12 hours from the following:12
Applications in Crew Resource Management
Human Factors in the Aviation/Aerospace Industry
Aviation/Aerospace System Safety
Aviation/Aerospace Safety Program Management
Data Analytics for Aviation Safety
Total Credits12

Cybersecurity Track

Electives - Select 12 hours from the following:12
Current Topics in Cybersecurity
System Exploitation and Penetration Testing
Multi-Agent Systems
Computer Security
Software Security Assessment
Applied Cryptography
Big Data Analytics for Cybersecurity
Data Compression for Image and Signal Processing
Total Credits12

High Performance Computing & Big Data Track 

Electives- Select 12 hours from the following:12
Data Compression for Image and Signal Processing
Fundamentals of Optimization
High Performance Scientific Computing
Statistical Quality Analysis
Complex Networks and Applications
Total Credits12

Homeland Security Track

Electives - Select 12 hours from the following:12
Data Analytics for Counterterrorism
Introduction to Human Security
The Internet, Security, and Governance
International Law and U.S. Security Policy
Principles of International Conflict Resolution
Environmental Security
Foundations of Resilience
Total Credits12

Human Factors Track

Electives - Select 12 hours from the following:12
Human Factors in Systems
Sensation and Perception
Memory and Cognition
User Experience
Human-Computer Interaction
Total Credits12
Capstone Project or Thesis3
Data Science Capstone Project
or CEDS 696 Co-Op Education Data Science
Track specific elective (Thesis) *
Total Credits3
Total Degree Credits30

MA 700 Thesis (registration of 6 hours, with the other 3 hours replacing one elective from chosen track)

Suggested Plan of Study

Year One
MA 506 Probability and Statistical Inference 3
CS 540 Database and Information Retrieval 3
DS 540 Data Mining 3
DS 544 Data Visualization 3
Specified Electives 6
 Credits Subtotal18.0
Year Two
DS 615 Data Modeling 3
MA 680 Data Science Capstone Project 3
Specified Electives 6
 Credits Subtotal12.0
 Credits Total: 30.0