The interdisciplinary Master of Science in Travel Technology and Analytics, offered jointly by the College of Engineering and Computer Science (Departments of Computer Science; Industrial Engineering and Management Systems; Civil, Environmental, and Construction Engineering) and the Rosen College of Hospitality Management (Departments of Tourism, Events, and Attractions; Hospitality Services), introduces graduate students to the technical aspects of big data analytics, including predictive analytics, algorithm design and models for SMART-cities, SMART-technologies and travel systems, and service systems quality engineering, in the specific context of global travel and tourism. The value and importance of such a program is demonstrated by travel and tourism and is the number one industry globally with immense economic, social, cultural and environmental impacts. Locally, the program promises to deliver significant value for the industry benefitting from a large number of visitors to the state and especially central Florida.
This powerful industry with $8.3 trillion in economic benefits globally, which functions at the intersection of engineering and management, is being transformed by rapidly increasing technological innovations and advances and is adapting to these changes by creating new employment opportunities to match. The dynamic nature of the industry and technological advances reveal the need for a workforce with advanced skills: fluency in data science and analytics, understanding of complex travel systems, strategic problem solving, big-picture thinking, technical knowledge, and practical skills aligned with technological advances. The changing nature of travel and tourism employment reveals emerging positions in areas of online travel agencies [OTA], global distribution systems [GDS], data analytics, data architecture, predictive analytics, mobile devices, travel apps, geolocation, data visualization, data translation, programming, interface design, virtual reality [VR], augmented reality [AR], hologram technology, travel click technology, business intelligence [BI], social media management, SMART-city design and development, and SMART-technologies and travel systems. The broader travel industry and its subsectors (transportation, lodging, and attractions) are experiencing the disruptive effects of direct and indirect distribution impacted by mobile devices, e-commerce, role of IT in distribution and dynamic pricing, and a highly perishable inventory (e.g., hotel rooms, airline seats) as well as those of artificial intelligence (AI) and machine learning and becoming increasingly more dependent on analytics as a key facet of business strategy.
Highlights:
- Academically-rich, industry-relevant interdisciplinary program
- Flexible course offerings in face-to-face, mixed and online modalities
- Offered at UCF's main campus and UCF's Rosen College of Hospitality Management campus
- Exponential industry growth locally, regionally, nationally and globally
- Cutting edge curriculum with a strong STEM foundation
- Research opportunities in both colleges
- Skills found highly desirable by industry leaders ranging from the local to the international level
Total Credit Hours Required: 30 Credit Hours Minimum beyond the Bachelor's Degree
Please note: Travel Technology and Analytics MS may be completed fully online, although not all elective options or program prerequisites may be offered online. Newly admitted students choosing to complete this program exclusively via UCF online classes may enroll with a reduction in campus-based fees.
International students (F or J visa) are required to enroll in a full-time course load of 9 credit hours during the fall and spring semesters. Only 3 of the 9 credit hours may be taken in a completely online format. For a detailed listing of enrollment requirements for international students, please visit . If you have questions, please consult UCF Global at 407-823-2337.
UCF is not authorized to provide online courses or instruction to students in some states. Refer to for current information.
Program Prerequisites
A Bachelor's degree in a STEM-related discipline from an accredited institution.
Depending on the degree completed, one or more prerequisite courses may be required, namely: STA 2023 (Statistical methods) and STA 3032 (Probability and Statistics for Engineers) or CAP 4630 (Artificial Intelligence).
Degree Requirements
Required Courses
18 Total Credits
- Complete all of the following
- Complete the following:
- HMG6449 - Smart Travel and Tourism (3)
- HMG6710 - International Tourism Management (3)
- ESI6261 - Service System Quality Engineering (3)
- TTE6667 - Discrete Choice Modeling in Transportation (3)
- TTE6608 - Algorithms and Models for Smart Cities (3)
- TTE6910 - Travel Technology and Analytics Capstone Course (3)
- Co-requisite Courses - HMG 6710 and HMG 6449
Electives
12 Total Credits
- Complete all of the following
Tourism and Hospitality Courses- Complete at least 2 of the following:
- HMG6291 - Hospitality Entrepreneurship: Concept Creation to Capitalization (3)
- HMG6446 - Hospitality/Tourism Information Technology (3)
- HMG6466 - Applied Revenue Management Techniques in Hospitality (3)
- HMG6556 - Digital Marketing and Big Data Management for Hospitality and Tourism (3)
- HMG6565 - Social Media in Hospitality and Tourism (3)
- HMG6566 - Principles of Destination Marketing and Management (3)
- HMG6585 - Data Analysis in Hospitality and Tourism Research (3)
- HMG6738 - Tourism Industry Analysis (3)
- HMG6251 - International Lodging Accommodations Analysis (3)
- HMG6347 - Contemporary Issues in the Resort Industry (3)
Technology Courses- Complete at least 2 of the following:
- CAP5610 - Machine Learning (3)
- CNT5008 - Computer Communication Networks Architecture (3)
- COP5711 - Parallel and Distributed Database Systems (3)
- COP6526 - Parallel and Cloud Computation (3)
- CGN6655 - Regional Planning, Design, and Development (3)
- EIN5117 - Management Information Systems I (3)
- ESI6224 - Quality Management (3)
- ESI6225 - Quality Design and Control (3)
- CGN5341 - Interdisciplinary Introduction to Smart Cities' Applications (3)
- CGN6343 - Cyber-Physical Systems and Smart Cities (3)
- CGN6342 - Modeling Human Behavior with Emerging Data (3)
- TTE6533 - Mobility in Smart Cities: Technologies and Application Areas (3)
Optional Elective Courses
0 Total Credits
- STA 5703 - Data Mining Methodology I 3 Credit Hours STA 6704 - Data Mining Methodology II 3 Credit Hours STA 5206 - Statistical Analysis 3 Credit Hours STA 6714 - Data Preparation 3 Credit Hours Any 5000 or 6000 level course in the College of Engineering with Program Director Approval (3 credits)
Grand Total Credits: 30
Application Requirements
Application Deadlines
Financial Information
Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies Funding website, which describes the types of financial assistance available at UCF and provides general guidance in planning your graduate finances. The Financial Information section of the Graduate Catalog is another key resource.
Fellowship Information
Fellowships are awarded to highly qualified students based on academic merit. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies. Fellowships are given to support a student's graduate study and do not have a work obligation. For more information, see UCF Graduate Fellowships, which includes descriptions of university fellowships and what students should do to be considered for a fellowship.
The program will be 30 credits (18 core/required and 12 electives). There will be no thesis requirement, however, a semester-long applied capstone project (involving industry and approved by the program director) will be required. The program will provide employable technical skills including the development of algorithms, discrete choice models, service systems quality engineering, machine learning, digital marketing, and big data management, and computer systems to extract insight from big data. The foregoing will be appropriately contextualized within the global travel industry and its trajectory toward increasing technological innovations that continue to drive the industry. The curriculum includes six (6) required courses that ensure that students have skills in algorithms and statistical techniques for extracting information in addition to awareness of the global travel and tourism industry including. Although courses can generally be taken in any order, the first two (2) required (co-requisite) courses serve as pre-requisites for all remaining courses in the program.
Admission Requirements
