Distance learning

Are you interested in taking graduate courses for credit in the traditional MS Degree Program of Systems Engineering and Management but cannot commit to traveling to campus on a regular basis? Distance learning may be the solution for you.


Distance learning offers great flexibility for working professionals:
• Courses run during the regular semester, in same-day synchronization with the class being offered on campus.
• Lectures delivered to UT Dallas students are recorded and streamed online, on the same day, but with access only by registered UT Dallas students.
• View the lectures at your convenience, any time day or night.
• Distance students will be required to come to campus only for exams and for occasional interactive sessions.
• Online teaching assistant (TA) help will be available.
• Both classes are core courses in the Systems Engineering and Management MS degree program ; other distance classes are planned for future semesters,
and a growing certificate program is available.Distance students register through the same process as other UT Dallas students, once they are admitted into the program as either degree-seeking or non-degree-seeking students.Contact Professor and Department Head Steve Yurkovich (steve.yurkovich@utdallas.edu) with questions.

Courses offered for Fall 2013

SYSM 6305 (3 credit hrs) – Optimization Theory and Practice

Optimization plays an important role in many fields, including all of engineering, computer science and machine learning, operations, finance, statistics, economics, etc. This course will provide students with a working knowledge of optimization theory, its numerical algorithms, and its applications. The course is divided into three main parts: linear programming (simplex method, duality theory), unconstrained methods (optimality conditions, descent algorithms and convergence theorems), and constrained minimization (Lagrange multipliers, Karush-Kuhn-Tucker conditions, active set, penalty and interior point methods). Practical applications from engineering, finance, statistics, etc., will be used throughout to complement the theory. Students will also use Matlab’s optimization toolbox to obtain practical experience with the material. Prerequisites: Students should have taken multivariable calculus and linear algebra. Open to all qualified graduate students and advanced undergraduate students. For more information, contact Prof. Jim Primbs (james.primbs@utdallas.edu)

SYSM 6302 (3 credit hrs)- Dynamics of Complex Networks and Systems

This course treats the dynamics of complex networks and systems with the goal of providing a basic understanding of the role and importance of complex networks on modern engineered systems. Examples of such systems are the Internet, the power grid, biological networks, financial networks, and others. Students will achieve a working knowledge of the fundamentals of graph theory and network theory, as well as an understanding of basic dynamical systems and stability theory. With the tools emphasized in this course, students will be able to model and analyze basic networks and dynamical systems and predict their behavior.
Prerequisites: Basic knowledge of linear algebra and differential equations required; some probability theory and knowledge of Matlab desirable. Open to all qualified graduate students and advanced undergraduate students. For course details, contact Prof. Mark Spong (mspong@utdallas.edu)