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.
Admission Deadlines: January 15 for international and July 15 for domestic applicants. Apply Now.
MST Degree Requirements
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.
- INFSCI 2300 - Human Information Processing
- INFSCI 2591 - Algorithm Design
- INFSCI 2710 - Database Management
- TELCOM 2310 - Applications of Networks
- TELCOM 2810 - Information Security and Privacy
MST Required Courses
- TELCOM 2120 - Network Performance
- TELCOM 2700 - Introduction to Wireless Networks
- TELCOM 2821 - Network Security
MST Required Seminar Course
Students in the MST degree program must take the following required course:
Students in the MST degree program must take two electives from the following list:
- INFSCI 2160 - Data Mining
- INFSCI 2595 - Machine Learning
- INFSCI 2750 - Cloud Computing
- TELCOM 2010 - Computer Networking Laboratory
- TELCOM 2125 - Network Science and Analysis
- TELCOM 2321 - Wide Area Networks
- TELCOM 2813 - Security Management and Computer Forensics
- TELCOM 2820 - Cryptography
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.
The MS Thesis Option
For students first enrolling in Fall 2022 and beyond
The overall goal of master’s thesis option is to provide students under the guidance of Thesis advisor and Thesis Committee with an opportunity to gain research experience, conduct an innovative research project, explore a focused topic area, improve publication records, and examine the suitability of pursuing a research and/or an academic career. A successful master thesis will generate high quality research publications, deepening understanding of a research topic, and increase the competitiveness in applying a PhD program within the University of Pittsburgh or other academic institutions.