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University of Pittsburgh    
2021-2022 Graduate & Professional Studies Catalog 
  Jun 16, 2024
2021-2022 Graduate & Professional Studies Catalog [Archived Catalog]

Telecommunications, MST

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Telecommunications now relies upon data analytics, machine learning, and information processing and how networks can serve humans - for example by enabling surgeons to perform remote surgery with low latency 5G networks. The Master of Science in Telecommunications (MST) program explores how information flows through networks to support human needs. Networks, traditionally the focus of phone service and then the internet, are now present in most aspects of our lives, from smart homes to cyber-physical systems. On a daily basis, communication and computer networks are utilized to support business operations, educational pursuits, health care, transportation networks, and social networks (both physical and virtual) for human well-being. The MST program is designed to produce telecommunications professionals who will design, build, secure, and manage networks and infrastructure that accommodate innovative usages of the networks by people, organizations, and businesses.

Graduates will gain a strong foundation in the design of network protocols, wireless networks, network security, and performance enhancement for communication networks. Coursework in data mining, machine learning, and algorithms prepares students for careers that call for maximizing network utilization, supporting information flow in the cloud, and tailoring networks to user needs and expectations. Graduates will have the skills and knowledge sought after by telecommunications equipment manufacturers, wireless providers, enterprise network users such as financial or pharmaceutical companies, and data center owners. Graduates also have chances to examine general network science and analysis to gain knowledge on emerging communication services from stand-alone streaming media to information flow on social networks.

Admissions Requirements

Applicants for graduate study must have earned a baccalaureate degree from an accredited college or university with a scholastic average of B (3.0 on a 4.0 scale) or better.

Prerequisites for admission to the MST degree program include one college course (3 credits or more) in each of the following (the corresponding Pitt course numbers are indicated):

  • Programming: A course on object-oriented programming using Java, C#, or C++. (CMPINF 0401 )
  • Probability and Statistics: A course covering data collection, descriptive and inferential statistics is optimal. It should cover measures of central tendency and variability, regression, correlation, non-parametric analysis, probability, and sampling, Bayesian analysis, significance tests, and hypothesis testing. (STAT 0200  or STAT 1000 )
  • Mathematics: A college-level mathematics course, in linear algebra, calculus, or discrete mathematics (MATH 0120 , MATH 0220 , or MATH 0400 )


Required Core Courses

All MST students are required to take the following five classes. Students must submit a petition to the faculty to waive any of the required core courses.

MST Required Courses

Students in the MST degree program must take the following three required courses:

MST Required Seminar Course

Students in the MST degree program must take the following required course:

Additional Approved Electives

Students may select two courses from the department’s standard graduate course offerings, including independent study and practicum experiences.

Students may also pursue opportunities that fall outside of the department’s standard graduate course offerings such as the Pittsburgh Council on Higher Education cross-registration, doctoral seminars, courses offered in other Pitt graduate departments, or undergraduate upper-level coursework in information science or computer science (1100-1999). These opportunities may not exceed six credits and require advisor approval prior to enrollment.

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