Master of Science in Computational Data Science (STEM) QS - Temple University, USA

Extract knowledge from big data with the Master of Science in Computational Data Science in Temple’s College of Science and Technology. You can enroll in the 30-credit-hour degree program as a part- or full-time student. Once you graduate, you’ll be prepared to fill the growing demand for data scientists in a range of industries from education to government. The program will also ready you for further graduate studies, research positions or teaching careers.

As a student, you’ll dig deep into computational analytics and explore techniques and theories steeped in computer science, mathematics and statistics. Throughout the program, you’ll learn how to analyze large quantities of data and discover the knowledge necessary to fuel cutting-edge developments. Data science is used to make complex decisions in a wide range of data-rich domains, such as biomedical science, defense and security, education, engineering, geoscience, physical science, and social science.

You’ll gain a strong foundation in algorithmic, computational and statistical thinking as well as the inner-workings of computer systems. Toward the end of the program, you will have the opportunity to pursue topics related to your academic and professional interests with the three-credit Master’s Project or the more advanced six-credit Master’s Thesis.

Areas of Specialization: Research interests of faculty include:

• Analysis of algorithms
• Artificial intelligence
• Communication and networks
• Computer architecture
• Data analytics
• Digital forensics
• Expert systems
• Flexible and intelligent manufacturing systems
• Graphics
• High-performance computing
• Information security and assurance
• Intelligent CAI systems
• Management information and database systems
• Natural language processing
• Network security
• Parallel and distributive processing and operating systems
• Programming languages
• Sensory and image processing
• Software engineering
• Theory of automata and computation
• Wired and wireless networks