Master of Engineering

Contacts

For program logistics, day-to-day assistance and non academic questions contact:

• Pamela Untalan - M.Eng Graduate Program Coordinator
• Laura Craft - M.Eng Graduate Program Coordinator (Accelerated 4+1 Students)

For academic advising, course selection, and degree progress contact your assigned advisor:

• Alexis Snyder - M.Eng Graduate Academic Advisor 
  • All International students 
  • Domestic at Alexandria Campus     
• Rebecca Stevenson - M.Eng Graduate Academic Advisor
  • Accelerated 4+1 Students
  • Domestic Blacksburg Students
  • Northrop Grumman Cohort Members
    

Program Tracks

The students in the MEng program have the option to choose one of the below tracks, and complete the MEng degree based on the requirements and recommendations provided for each track. Total number of required credits to graduate with the MEng degree is 30 credits.

Project Enhanced Track: 

Provides flexibility in electives while emphasizing CS in a project context.

Required Courses (6 or 9 credits)*:

• CS5024: Ethics & Professionalism in CS  (3 credits)
• CS5934: Capstone Design (3 credits)
• CS5040: Intermediate Data Structures and Algorithm Design* (3 credits)

Elective Courses (24 or 21 credits)*:

• Students have the option to choose two focus areas from the list below or tailor courses towards their own goals. 

* _{CS5040 may be waived at admission and replaced by another graduate level elective course. This is typical for students with a CS undergraduate degree or minor.} 

Project Intensive Track: 

Emphasizes a deep project experience and structured development work. Project work integrates ethics and project management.

Required Courses (12 or 15 credits)*:

• CS 5925: Integrated Project Design 1  (6 credits)
  
• CS 5926: Integrated Project Design 2  (6 credits)
• CS 5040: Intermediate Data Structures and Algorithm Design* (3 credits)

Elective Courses (18 or 15 credits)*:

• Students have the option to choose one or two focus areas from the list below or tailor courses towards their own goals. 

* _{CS5040 may be waived at admission and replaced by another graduate level elective course. This is typical for students with a CS undergraduate degree or minor.} 

Focus Areas

Most students will choose two focus areas to build a clear technical direction. Each focus area has three core courses. For the most accurate list of course offerings, consult the Virginia Tech Timetable of Classes.

Applied AI and Machine Learning: Build AI-enabled solutions for real-world problems

Human-Centered Computing: Make complex technology intuitive and human-centered

Cybersecurity: Protect systems and data from modern threats

Software Systems: Design and deploy scalable software systems

Emerging Technologies: Strengthen core computing theory & practice

Computer Systems and Architecture: Build and optimize large-scale computing infrastructure 

Elective Courses Guidelines:

• Choose from the list of graduate courses
• Maximum of six credits at the 4000 level (list of 4000 level courses).
  
• All courses must be in CS, except one course from an outside department from the approved cognate course list
• Credits from 4000-level courses on the cognate list and most CS4xxx courses can be used for graduate credit, except CS4944, CS4964, CS4974 and CS 4994.
• CS5894 Final Examination, CS5904 Project and Report, CS5944 Graduate Seminar, CS5974 Independent Study, CS5994 Research and Thesis, and CS7994 Research and Dissertation cannot be used to satisfy any MEng credit requirements.
• Note that students may not receive credit for both CS3114 and CS5040.

Background Requirements

Students are required to have as a minimum a course on their transcript that is equivalent to CS5020 or CS2114. Similar courses are taught at nearly all universities and colleges. Consult VT Undergraduate Transfer Equivalency Database to find CS2114 equivalent courses at other institutions.

Students are strongly advised to have proficiency in the Java programming language prior to attempting CS5040. Students need to be ready for CS5040 – Intermediate Data Structures and Algorithm Analysis, which relies heavily on object oriented design design, data structures concepts and Java Programming. They also need serious practice with writing programs of the appropriate scale, which means significant programming practice.

While not required for entry into the program, other useful background would be a Discrete Math course, and a course in basic Computer Architecture or Computer Organization, similar to CS2505.