Master of Science in
Data Science

This program is designed to prepare students to use the latest computational and analytical tools to solve data intensive problems in business, industry or government.

In the era of the big data revolution, deriving insights from available information to support or optimize decisions is becoming a necessity in businesses, industries and governments.

Embry‑Riddle’s Master of Science in Data Science (MSDS) is designed to provide students with:

Practical skills needed to lead the industry into the future.
The ability to transform ubiquitous data into relatable, actionable decisions.
Strategies to combine data understanding, analytical skills and domain knowledge to overcome challenges.

Whether you seek to enhance your marketability in the fields of safety, cybersecurity, business, homeland security or a broader area, the MSDS will prepare you for success in your career.

Embry‑Riddle graduates are trained to employ the most powerful computational and analytic tools to meet complex challenges facing the industry today.

According to the U.S .Bureau of Labor Statistics, the field of data science is expected to grow by 36% by 2031, much faster than the national average.

Data Science graduates are in high demand in a vast array of industries, including:

Aviation & Aerospace
Business
Cybersecurity
Homeland Security
Safety & Security

Interdisciplinary coursework, world-renowned faculty and state-of-the-art labs prepare students to work collaboratively within distinct tracks of data specialization.

Learn more about data science career opportunities.

DETAILS

About Data Science at the Daytona Beach, FL Campus

Why pursue a degree in Data Science?

The goal of the M.S. in Data Science degree program is to provide the students with the knowledge and skills of data collection, pre-processing, analysis, visualization and ethical implication associated with big data arising within the various domain areas.

What does data science coursework include?

All the core courses within the degree program are project-based allowing for hands-on experience culminating in a final capstone project or an internship in the student’s chosen domain area. Internships provide the opportunity to earn real-world experience and equips students to communicate effectively with data visualization.

Learn more about the Department of Mathematics

What areas of data science are available for specialization?

The program offers the flexibility for students to choose one of the five data science specialization tracks:

Aviation Safety
Aviation Business
High Performance Computing & Big Data
Cybersecurity
Homeland Security

Learn more about the Daytona Beach, FL Campus

Student Learning Outcomes

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 540	Database and Information Retrieval	3
DS 540	Data Mining	3
DS 544	Data Visualization	3
DS 615	Data Modeling	3
MA 506	Probability and Statistical Inference	3
Total Credits		15

Aerospace Engineering Track

Required Courses
AE 514	Introduction to the Finite Element Method	3
AE 516	Computational Aeronautical Fluid Dynamics	3
AE 523	Linear Systems	3
Select one of the following:		3
AE 5XX Aerospace Engineering Elective
EP 501	Numerical Methods for Engineers and Scientists
MA 532	Numerical Linear Algebra for Engineers
Total Credits		12

Aviation Business Track


Electives - Select 12 hours from the following:		12
ACC 517	Accounting for Decision Making
BA 511	Operations Research
BA 523	Advanced Aviation Economics
BA 610	Airline Optimization and Simulation Systems
BA 612	Data Analytics for Aviation Business
BA 645	Airport Operations and Management
FIN 518	Managerial Finance
FIN 621	International Aviation Finance
FIN 623	Aircraft Funding Legal and Financial Analysis
Total Credits		12

Aviation Safety Track

Electives - Select 12 hours from the following:		12
MSA 516	Applications in Crew Resource Management
MSA 545	Human Factors in the Aviation/Aerospace Industry
MSA 611	Aviation/Aerospace System Safety
MSA 621	Aviation/Aerospace Safety Program Management
MSA 628	Data Analytics for Aviation Safety
Total Credits		12

Cybersecurity Track


Electives - Select 12 hours from the following:		12
CS 525	Current Topics in Cybersecurity
CS 527	System Exploitation and Penetration Testing
CS 528	Multi-Agent Systems
CS 529	Computer Security
CS 532	Software Security Assessment
CS 538	Applied Cryptography
CS 602	Big Data Analytics for Cybersecurity
DS 625	Data Compression for Image and Signal Processing
Total Credits		12

High Performance Computing & Big Data Track

Electives- Select 12 hours from the following:		12
DS 625	Data Compression for Image and Signal Processing
MA 510	Fundamentals of Optimization
MA 553	High Performance Scientific Computing
MA 605	Statistical Quality Analysis
MA 630	Complex Networks and Applications
MA 532	Numerical Linear Algebra for Engineers
Total Credits		12

Homeland Security Track

Electives - Select 12 hours from the following:		12
HS 602	Data Analytics for Counterterrorism
MHSR 500	Introduction to Human Security
MHSR 511	The Internet, Security, and Governance
MHSR 515	International Law and U.S. Security Policy
MHSR 520	Principles of International Conflict Resolution
MHSR 530	Environmental Security
MHSR 540	Foundations of Resilience
Total Credits		12

Human Factors Track

Electives - Select 12 hours from the following:		12
HFS 515	Ergonomics
HFS 600	Human Factors in Systems
HFS 615	Sensation and Perception
HFS 620	Memory and Cognition
HFS 624	User Experience
HFS 635	Human-Computer Interaction
Total Credits		12

Capstone Project or Thesis		3
MA 680	Data Science Capstone Project
or CEDS 696 Co-Op Education Data Science
Track specific elective (Thesis) ^*
Total Credits		3

Total Degree Credits

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

Suggested Plan of Study

Year One
		Credits
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 Subtotal	18.0
Year Two
DS 615	Data Modeling	3
MA 680	Data Science Capstone Project	3
	Specified Electives	6
	Credits Subtotal	12.0
	Credits Total:	30.0

For course descriptions, education requirements, curriculum, and suggested plan of study, please see the Master of Science in Data Science in the Daytona Beach Catalog.

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Summary

30 Credits

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At Embry-Riddle's Cyber Rodeo, Electrical Engineering and Computer Science student Logan Luna (center) presents research on a cybersecurity defense system that autonomously adapts to new threats. To his left is fellow Electrical Engineering and Computer Science student Matt Berkowitz, who also worked on the project.

Daytona Beach Campus hosts Cybersecurity Researchers

CyBASE performs research in cybersecurity associated with critical infrastructures and assured systems.

Master of Science in
Data Science

Embry‑Riddle’s Master of Science in Data Science (MSDS) is designed to provide students with:

Data Science graduates are in high demand in a vast array of industries, including:

DETAILS