Duluth campus

This is archival data. This system was retired as of August 21, 2023 and the information on this page has not been updated since then. For current information, visit catalogs.umn.edu.

 
Duluth Campus

Computer Science M.S.

Computer Science
Swenson College of Science and Engineering
Link to a list of faculty for this program.
Contact Information
Department of Computer Science, University of Minnesota Duluth, 1114 Kirby Drive, 320 Heller Hall, Duluth, MN 55812 (218-726-7607; fax: 218-726-8240)
Email: cs@d.umn.edu
Website: http://www.d.umn.edu/cs/degrees/grad/
  • Program Type: Master's
  • Requirements for this program are current for Fall 2020
  • Length of program in credits: 30 to 32
  • This program does not require summer semesters for timely completion.
  • Degree: Master of Science
Along with the program-specific requirements listed below, please read the General Information section of this website for requirements that apply to all major fields.
Computer science is a discipline that involves understanding the design of computers and computational processes. Study in the field ranges from the theoretical study of algorithms to the design and implementation of software at the systems and applications levels. The master of science is a two-year program that provides the necessary foundational studies for graduates planning to pursue either a doctorate in computer science or a career as a computer scientist in business or industry. It is designed for students with undergraduate degrees in computer science or a related field. These students should be able to enroll immediately in 5xxx or 8xxx computer science courses.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
Prerequisites for Admission
The preferred undergraduate GPA for admittance to the program is 3.00.
The program is designed for students with undergraduate degrees in computer science or a related field.
Other requirements to be completed before admission:
Students with undergraduate degrees in fields other than computer science or related areas may be considered for admittance if they have completed the following courses or their equivalents: CS 1511-1521 - Computer Science I-II; CS 2511 - Software Analysis and Design; CS 2521 - Computer Organization and Architecture; MATH 3355 - Discrete Mathematics or CS 2531 - Discrete Structures for Computer Science' CS 3531 Automata & Formal Languages; and at least three of CS 4312 - Operating Systems, CS 4332 - Computer Security, CS 4422 - Computer Networks, CS 4122 - Advanced Data Structures and Algorithms, CS 4212 - Computer Graphics, CS 4322 - Database Management Systems. The appropriate math prerequisites, namely MATH 1296 - Calculus I and STAT 3611 - Introduction to Probability and Statistics, are also required.
Applicants must submit their test score(s) from the following:
  • GRE
International applicants must submit score(s) from one of the following tests:
  • TOEFL
    • Internet Based - Total Score: 79
    • Internet Based - Writing Score: 21
    • Internet Based - Reading Score: 19
  • IELTS
    • Total Score: 6.5
  • MELAB
    • Final score: 80
The preferred English language test is Test of English as Foreign Language.
Key to test abbreviations (GRE, TOEFL, IELTS, MELAB).
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
Plan A: Plan A requires 14 to 20 major credits, 0 to 6 credits outside the major, and 10 thesis credits. The final exam is oral.
Plan B: Plan B requires 18 to 32 major credits and 0 to 8 credits outside the major. The final exam is oral. A capstone project is required.
Capstone Project:4 project credits are required.
This program may be completed with a minor.
Use of 4xxx courses toward program requirements is permitted under certain conditions with adviser approval.
A minimum GPA of 3.00 is required for students to remain in good standing.
1. Use of 4xxx courses toward program requirements is permitted under certain conditions with adviser and director of graduate studies approval. 2. A minimum GPA of 3.00 is required for students to remain in good standing. 3. The master of science degree is offered under Plan A (thesis) and Plan B (non-thesis). At least 30 credits are required, including 12 credits from 5xxx courses or higher in computer science, 1 credit of CS 8993 Seminar each year for a total of 2 credits, and 6 credits of electives (either any 5xxx or higher courses). 4. Plan A also requires 10 thesis credits (CS 8777). 5. Plan B also requires at least 8 credits in additional courses, 5xxx or above, as well as 4 project credits (CS 8555). Except in very rare instances, the 8 credits of additional courses for Plan B must be computer science courses. 6. All courses are chosen in consultation with the student's adviser, subject to approval by the director of graduate studies. Because of this, Plan B students may want to consider filling their 6 Electives requirement credits from outside CS. 7. Normally 4xxx computer science courses may not be included in degree programs for the master of science in computer science.
Computer Science requirement (14 cr)
Take 12 or more credit(s) from the following:
· CS 5112 - Advanced Theory of Computation (4.0 cr)
· CS 5122 - Advanced Algorithms and Data Structures (4.0 cr)
· CS 5212 - Computer Graphics (4.0 cr)
· CS 5222 - Artificial Intelligence (4.0 cr)
· CS 5232 - Introduction to Machine Learning and Data Mining (4.0 cr)
· CS 5242 - Natural Language Processing (4.0 cr)
· CS 5312 - Operating Systems (4.0 cr)
· CS 5322 - Database Management Systems (4.0 cr)
· CS 5332 - Computer Security (4.0 cr)
· CS 5342 - Compiler Design (4.0 cr)
· CS 5412 - Computer Architecture (4.0 cr)
· CS 5422 - Computer Networks (4.0 cr)
· CS 5612 {Inactive} (4.0 cr)
· CS 5642 - Advanced Natural Language Processing (4.0 cr)
· CS 5652 {Inactive} (4.0 cr)
· CS 5732 - Advanced Computer Security (4.0 cr)
Graduate Seminar
Take 2 credits, 1 in first Fall semester and 1 in second fall semester, of graduate seminar.
CS 8993 - Seminar (1.0 cr)
Electives (6 cr)
The purpose of this requirement is to provide coursework that will support your degree program without duplicating or overlapping courses available within the graduate CS curriculum. Such courses may be chosen from any 5xxx or higher courses subject to the approval of the director of graduate studies.
Plan A or Plan B (10 - 12 cr)
Plan A
Students must register for 10 credits.
CS 8777 - Thesis Credits: Master's (1.0-24.0 cr)
or Plan B
Students must complete an approved Plan B Project through registration of 4 credits of CS 8794 - Project Credits: Master's. Master's Plan B Projects represent a significant programming research project that often will extend a large assignment within a 5xxx-level or higher course. Speak to the instructors of 5xxx-level or higher courses to see if the course supports Master's Projects.
Take 4 or more credit(s) from the following:
· CS 8794 - Project Credits: Master's (1.0-4.0 cr)
Any CS 5xxx or higher courses, subject to approval by the director of graduate studies.
Take 8 or more credit(s) from the following:
· CS 5xxx
· CS 8xxx
 
More program views..
View college catalog(s):
· Swenson College of Science and Engineering

View future requirement(s):
· Fall 2023
· Fall 2022


View checkpoint chart:
· Computer Science M.S.
View PDF Version:
Search.
Search Programs

Search University Catalogs
Related links.

Swenson College of Science and Engineering

Graduate Admissions

Graduate School Fellowships

Graduate Assistantships

Colleges and Schools

One Stop
for tuition, course registration, financial aid, academic calendars, and more
 
CS 5112 - Advanced Theory of Computation
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Mathematical theory of computation and complexity. Deterministic and nondeterministic Turing machines, Church-Turing Thesis, recursive and recursively enumerable languages. Lambda calculus. Undecidable problems, Rice's Theorem, undecidability of first-order logic and Gödels incompleteness theorem. Time and space complexity, reducibility, completeness for complexity classes, Cook's Theorem, P versus NP, Savitch's Theorem, complexity hierarchy. pre-req: Grad student, CS 3512 or 3531 or instructor consent
CS 5122 - Advanced Algorithms and Data Structures
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Survey of advanced data structures and algorithms such as heaps and heapsort, quicksort, red-black trees, B-tress, hash tables, graph algorithms, divide and conquer algorithms, dynamic programming, and greedy algorithms. Methods for proving correctness and asymptotic analysis. pre-req: grad student; CS 2511, 2531 or 3512 or MATH 3355 or instructor consent; a grade of C- or better in all prerequisite courses
CS 5212 - Computer Graphics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduces the fundamentals of computer graphics to create 2D images from 3D data representations, the graphics pipeline, 3D representations of objects such as triangles and triangle meshes, surface material representations, color representation, vector and matrix mathematics, 3D coordinates and transformations, transport of light energy, global illumination, graphics rendering systemes, ray tracing, rasterization, real-time rendering, OpenGL and computer graphics hardware. prereq: graduate student, CS 2511, (2531 or 3512 or MATH 3355), (MATH 3280 or 3326) or instructor consent, a grade of C- or better is required in all prerequisite courses
CS 5222 - Artificial Intelligence
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Principles and programming methods of artificial intelligence. Knowledge representation methods, state space search strategies, and use of logic for problem solving. Applications chosen from among expert systems, planning, natural language understanding, uncertainty reasoning, machine learning, and robotics. Lectures and labs will utilize suitable high-level languages (e.g., Python or Lisp). prereq: grad student, 2511, (2531 or 3512 or MATH 3355) or instructor consent, a grade of C- or better is required in all prerequisite courses
CS 5232 - Introduction to Machine Learning and Data Mining
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to primary approaches to machine learning and data mining. Methods selected from decision trees, neural networks, statistical learning, genetic algorithms, support vector machines, ensemble methods, and reinforcement learning. Theoretical concepts associated with learning, such as inductive bias and Occam's razor. This is a potential Master's project course. prereq: grad student, 2511, 2531 or 3512 or MATH 3355, Stat 3611 or 3411, Math 3280 or 3326 or instructor consent; a grade of C- or better is required in all prerequisite courses
CS 5242 - Natural Language Processing
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Techniques for creating computer programs that analyze, generate, and understand written human language. Emphasizes broad coverage of both rule-based and empirical data-driven methods. Topics include word-level approaches, syntactic analysis, and semantic interpretation. Applications selected from conversational agents, sentiment analysis, information extraction, and question answering. Significant research project that includes experimental results, written report, and clear grasp of ethical considerations involved. prereq: CS 2511, (2531 or 3512 or MATH 3355), grad student or instructor consent; a grade of C- or better is required in the prerequisite course; credit will not be granted if already received for CS 4242 or 5761
CS 5312 - Operating Systems
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Operating system as resource manager. Modern solutions to issues such as processor management and scheduling, concurrency and related problems including deadlocks, memory management and protection, file system design, virtualization, distributed and cloud computing. Concepts including concurrency are illustrated via laboratory assignments, This is a potential Master's project course. prereq: grad student, 2511, 2521, (2531 or 3512 or MATH 3355) or instructor consent, a grade of C- or better is required in all prerequisite courses
CS 5322 - Database Management Systems
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Entropy and the underlying characteristics of text. Encryption-basic techniques based on confusion and diffusion and modern day encryption. Access, information flow and inference control. Program threats and intrusion detection/prevention. Network and Internet security. Firewalls, trusted systems, network authentication. Privacy and related social issues. Planning, Incidents, and Recovery. prereq: grad student, 2511, 2521, (2531 or 3512 or MATH 3355) or instructor consent; a grade of C- or better is required in all prerequisite courses
CS 5332 - Computer Security
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Entropy and the underlying characteristics of text. Encryption-basic techniques based on confusion and diffusion and modern day encryption. Access, information flow and inference control. Program threats and intrusion detection/prevention. Network and Internet security. Firewalls, trusted systems, network authentication. Privacy and related social issues. Planning, Incidents, and Recovery. prereq: grad student, 2511, 2521, (2531 or 3512 or MATH 3355) or instructor consent; a grade of C- or better is required in all prerequisite courses
CS 5342 - Compiler Design
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
A selection from the following topics: finite-state grammars, lexical analysis, and implementation of symbol tables. Context-free languages and parsing techniques. Syntax-directed translation. Run-time storage allocation. Intermediate languages. Code generation methods. Local and global optimization techniques. prereq: grad student, 2511, 2521, (2531 or 3512 or MATH 3355) or instructor consent, a grade of C- or better is required in all prerequisite courses
CS 5412 - Computer Architecture
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Broad coverage of computer architecture, with a focus on the development of the stored program computer and the historical evolution of architectures. Includes coverage of significant architectures based on vacuum tubes, transistors, and integrated circuits. Impact of Moore?s Law and possible paradigms for the future including quantum and molecular computing. prereq: 2521, (2531 or 3512 or MATH 3355), grad student or instructor consent, a grade of C- or better is required in all prerequisite courses
CS 5422 - Computer Networks
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to computer networking, network programming, networking hardware and associated network protocols. Layered network architecture, network services, and implementation of computer networking software. prereq: grad student, 2511, 2521, (2531 or 3512 or MATH 3355) or instructor consent, a grade of C- or better is required in all prerequisite courses
CS 5642 - Advanced Natural Language Processing
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Advanced techniques for creating computer programs that analyze, generage, and understand written human language. Emphasizes current empirical data-driven methods. Topics include sentence level representations, vector semantics, and models of document understanding. Applications selected from word sense discovery, machine translation, sentiment and option mining, and social computing. Significant research project that includes experimental results, written report, and clear grasp of ethical considerations involved. pre-req: CS 4242 or 5242, grad student or instructor consent; a grade of C- or better is required in the prerequisite course.
CS 5732 - Advanced Computer Security
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Broad, active, hands-on and implementation-based approach to computer security. Fundamental cryptographic theory, advanced techniques and application. Complexity, cryptanalysis, and impact of technological change. Core security theory; confidentiality, integrity, availability. Security models. Risk assessment and decision-making. Issues for general -purpose, trusted and cloud operating system security including hardware requirements, authentication, access control, information flow and assurance. Program and network security fundamentals and best practices including coding principles, firewalls and network design. Exploits, defenses and remediation for multiple issues pertaining to software, hardware, databases and networks. Political, social and engineering issues relating to security and privacy. prereq: CS 4821, grad student and instructor consent
CS 8993 - Seminar
Credits: 1.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Presentation and discussion of basic ethical theories, case studies dealing with ethical issues facing the computing professional in his/her life as a practitioner, and the development of research proposal which meets the requirements and standards of the department and serves as the foundation of and guideline for the development of the graduate research project (i.e., thesis). prereq: instructor consent
CS 8777 - Thesis Credits: Master's
Credits: 1.0 -24.0 [max 50.0]
Grading Basis: No Grade
Typically offered: Every Fall & Spring
(No description) prereq: Max 18 cr per semester or summer; 10 cr total required (Plan A only)
CS 8794 - Project Credits: Master's
Credits: 1.0 -4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Project credit requirements for the Master's Degree with Project Plan B. Independent research performed under Advisor's supervision. pre-req: graduate student, advisor's consent