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.
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
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 | |
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 | 30 |
- *
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 |
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Summary
30 Credits
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