The Computer Science program will introduce you to core areas of advanced computing architecture, advanced operating systems and theories and algorithms used in computing. You will conduct advanced research in software engineering, systems or artificial intelligence as you learn high-demand skills sought by industry.
Program Highlights
State-of-the-art computing facilities including the Integrated Engineering Science and Laboratory Facility (ISELF) Visualization Lab, Sunfire 280R running Solaris, several workstations running Windows and Linux and supercomputing facilities in the Twin Cities.
Five to seven graduate assistantship positions each year.
Research and project labs are equipped with Sun, Silicon Graphics and DEC Alpha workstations.
Program is offered on a part-time or full-time track.
Program Distinctions
Graduates have gone on to work for Amazon, Google, Guidant, Medtronics, IBM, Beckman Coulter and Thomson Reuters among others. They have also continued on to Ph.D. programs where they have been awarded assistantships.
Taught by 13 internationally-recognized faculty members.
Requirements and Details
The GRE is required.
A strong showing (more than 75th percentile) in the quantitative GRE score is essential.
A strong score in the verbal section is also important.
Admission is competitive.
Positive letters of recommendation are important, as is a solid undergraduate academic record.
Lack of a computer science background is usually not a major concern, since prerequisite courses are prescribed. However, a background in the sciences and mathematics is essential.
Admission decisions are made at specific times associated with the application deadlines, usually in the week following the deadlines.
A final admission decision may take up to three weeks to receive from the application deadline and up to ten weeks for I-20s to be issued to international students.
Fully-qualified applicants will have taken courses that cover the following topics:
Non-linear data structures: sorting and searching algorithms.
Computer architecture: hardware organization, I/O interface, interrupt mechanisms and pipeline processor design.
File systems; hashed indexed, ISAM files; B-trees; external sorting.
Programming languages: design and implementation.
Operating systems: process, memory and file system management, device handlers.
Finite mathematics and modern algebra.
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