Computer Science
Undergraduate Programs
Description
Computer Science prepares graduates for top industry positions in computing and for graduate study. Computer science as a field spans a wide range of subjects from theoretical and algorithmic foundations to cutting-edge developments in cloud computing, data science, data engineering, networks, operating systems, distributed systems, machine learning, artificial intelligence, and robotics.
This upper-division program is entirely project-based. Students earn their degrees by completing four semester-long team projects that come from industry or academic partners, or their own entrepreneurial ideas. Project solutions require knowledge from multiple aspects of computer science as well as a wide array of professional skills. Technical course content and professional skills training are integrated through application in projects. Faculty coaches and industry mentors support all technical and professionalism aspects of student work. Students at different stages in their degrees pool their knowledge and experience as they collaborate on project teams.
A computer science minor prepares students to apply the tools and theory of computer science to their major field of study. Applications in art, biology, physics, chemistry, engineering, cognitive science, music, and the social sciences all benefit from a deeper understanding of computer science.
Majors |
Program | Locations | Major / Total Credits |
|---|---|---|---|
| Computer Science BS | BS - Bachelor of Science |
|
76 / 120 |
Minors |
Program | Locations | Total Credits |
|---|---|---|---|
| Computer Science Minor |
|
28 |
Policies & Faculty
Policies
Admission to the Major is required before students are permitted to take 300- and 400-level courses in computer science.
Students with declared majors in computer engineering or cognitive science or with a declared computer science minor will be given permission to take upper-division required or elective computer science courses where they meet the pre-requisites.
Application to Major.
To be considered for admission to the computer science major, the student must meet the following requirements:
- Completion of ENG 101, CIS 223, CIS 224 and MATH 280 with grades of "C" or better.
- A cumulative GPA of 2.5 or higher in required lower-division Math and CIS courses (or their equivalents).
- Completion of an application form including essay(s) and a letter of recommendation.
Admission to the Computer Science upper-division program is selective and subject to the approval of the Computer Science program faculty. Admission to the Computer Science program also requires the completion of the application found at the following website: https://cset.mnsu.edu/cs. Each application will be evaluated individually and the decision of Computer Science program faculty will be final. Failure to submit an application by stated deadline could result in the student being denied admission to the program. If a student is denied admission to the Computer Science Program, he/she can reapply to the program for admission in subsequent years.
A. Minnesota State Mankato students. This application form (https://cset.mnsu.edu/cs) is submitted to the Computer Science program along with a copy of the student's Minnesota State Mankato transcript and any transfer evaluations. Lower-division computer science students at Minnesota State Mankato are not guaranteed admission to the program.
B. Transfer Students. Transfer students must submit an application to Minnesota State Mankato and follow all transfer policies. Students may be able to complete the required lower-division computer science curriculum at another college or university and have these courses and credits transferred to Minnesota State Mankato, when applying for admission to the Computer Science Program. Along with applying to the University, students must apply directly to the program using this application form (https://cset.mnsu.edu/cs), which is submitted to the Computer Science program along with an unofficial copy of the student's transcripts.
GPA Policy.
A GPA of 2.5 or higher in courses required for a major or minor in Computer Science is required for graduation. This GPA requirement is calculated and must be maintained for each of the following areas: 1) for the combined Required General Education and Required Support Courses, or their substitutions, if any; 2) for the Required for Major, Required Electives courses and Minor courses. Refer to the College regarding required advising for students on academic probation.
Grading Policy.
All coursework applied towards the major or minor, including required general education and support courses, must be taken for a letter grade except for courses offered only as P/N. A minimum grade of "C-" is required in all courses which are to be applied towards a departmental major or minor program, including those required courses which are in supporting areas (such as ENG 271W or Comm 100). In addition, a minimum grade of "C-" is required for all prerequisite courses unless a higher grade is noted in the admission requirements. Grades of "D" are not accepted by the department.
Incomplete Policy.
An incomplete grade for a course will generally be given only under two conditions. The first condition is illness — a doctor's written recommendation must be supplied. The second condition arises when a death in the student's family has caused the student to be away from the campus for an extended period of time. The student must have a satisfactory grade ("C-" or better) in the course at the time of the onset of the condition.
Residency.
At least 50 percent of the computer science credits required for a major or minor from this department must be earned at Minnesota State University, Mankato. Completion of the degree requires completion of four projects.
Contact Information
273 Wissink Hall
CIS Department Office (507) 389-1412http://cset.mnsu.edu/cs
https://cset.mnsu.edu/departments/computer-information-science/
Faculty
CS Advisor
- Rebecca Bates, PhD
CS Program Director/CS Advisor
- Lin Chase, PhD
CS Advisor
- Jonathan Hardwick, PhD
CS Advisor
- Guarionex Salivia, PhD
CS Advisor
- Rushit Dave, PhD
Chair Computer Information Science
- Jonathan Hardwick, PhD
Faculty
200 Level
Credits: 4
Course will explore the interplay between science fiction (1950s-present) and the development of artificial intelligence. Turing tests, agents, senses, problem solving, game playing, information retrieval, machine translation robotics, and ethical issues. VariablePrerequisites: none
Goal Areas: GE-06, GE-09
Credits: 4
Fundamentals of data mining and knowledge discovery. Methods include decision tree algorithms, association rule generators, neural networks, and web-based mining. Rule-based systems and intelligent agents are introduced. Students learn how to apply data-mining tools to real-world problems.Prerequisites: CIS 121
Credits: 3
An introduction to graphical programming environments. Topics include data and data types, repetition, selection, data acquisition, data dependency, efficiency, modular program construction, array processing, debugging, and visualization.Prerequisites: EET 113, MATH 121
Credits: 1-3
Workshop topics will be announced. Workshops on different topics may be taken for credit.Prerequisites: Consent of instructor
Credits: 1
Provides students interested in a computer science major or minor an opportunity to explore topics not normally covered in the curriculum. Speakers will include faculty, graduate students, undergraduate students admitted to the Computer Science major, visiting researchers and industry members.Fall, SpringPrerequisites: none
Credits: 1-2
Special topics not covered in other 100 or 200-level courses. May be repeated for each new topic.VariablePrerequisites: none
300 Level
Credits: 2
This course introduces the foundational concepts of operating systems including operating systems principles, concurrency, scheduling, dispatch, and memory management and prepares students for advanced topics in operating systems.Prerequisites: CIS 223, CIS 224 or EE 234, and admission to major.
Credits: 2
This course introduces the foundational concepts of software engineering, and parallel and distributed computing and prepares students for advanced topics in these areas.Prerequisites: CIS 223, CIS 224, and admission to major.
Credits: 2
This course introduces the foundational concepts of programming languages, including the principles of language design, language constructs, and comparison of major languages. Topics include formal methods of examining syntax and semantics of languages and lexical analysis of language components and constructs, and propositional and predicate calculi.Prerequisites: CIS 223, CIS 224, and admission to major.
Credits: 2
This course introduces the foundational concepts of Information Management, Database Systems, Data Modeling, Data Security, Secure Design, Defensive Programming, Security and Cryptography.Prerequisites: CIS 223, CIS 224, and admission to major.
Credits: 2
An introduction to data communications and networks. The field encompasses local area networks, wide area networks, and wireless communication. Topics include digital signals, transmission techniques, error detection and correction, OSI model, TCP/IP model, network topologies, network protocols, and communications hardware.Prerequisites: CIS 223 and CIS 224 or EE 234
Credits: 2
This course covers more advanced algorithmic areas, including tree, graph, and text algorithms, as well as the study of algorithmic strategies (e.g., divide-and-conquer, linear programming, etc.). There is an emphasis on the application of efficient algorithms to solve novel problems, and the development of an algorithmic mindset by students. Admission to Major or Permission.Prerequisites: none
Credits: 4
Students learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.Prerequisites: CIS 223 and MATH 280
Credits: 4
Students learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.Prerequisites: CIS 223 and MATH 280
Credits: 4
Students further learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students continue to learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.Prerequisites: CS 391
Credits: 4
Students further learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students continue to learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.Prerequisites: CS 391W
400 Level
Credits: 2
Study of theory and/or implementation topics related to operating systems such as security and protection, virtual machines, device management, file systems, real time and embedded systems, fault tolerance and system performance evaluation. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 2
Study of theory and/or implementation topics related to programming languages such as syntax analysis, semantic analysis, code generation, runtime systems, static analysis, advanced programming constructs, concurrency and parallelism, type systems, formal semantics, language pragmatics, and logic programming. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 2
Study of theory and/or implementation topics related to networking and computation such as mobility and social networking and expansion of topics covered in CS 306. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 2
Study of theory and/or implementation topics related to algorithms and computing such as advanced computational complexity, automata theory and computability, and advanced data structures algorithms and analysis. This includes the theoretical underpinnings of modern computer science, focusing on three main models of computation: DFA, PDA and Turing Machines. Students determine model capabilities and limitations: what is and is not computable by each of them.Prerequisites: Admission to major or permission.
Credits: 2
Study of theory and/or implementation topics related to parallel and distributed computing such as parallel algorithms, architecture, and performance, distributed systems, cloud computing, and formal models and semantics. These have been called techniques for High Performance Computing. Topics also include application areas and basic concepts of parallel computing, hardware design of modern HPC platforms and parallel programming models, methods of measuring and characterizing serial and parallel performance.Prerequisites: Admission to major or permission.
Credits: 2
Study of theory and/or implementation topics related to computer architecture and organization such as functional organization, multiprocessing and alternative architectures, and performance enhancements. This includes topics in computer architecture including a major emphasis on measuring and improving computer performance. Topics include advances in pipelining and analysis and optimization of storage systems and networks, multiprocessor challenges and trends.Prerequisites: Admission to major or permission.
Credits: 2
Study of theory and/or implementation topics related to intelligent systems such as Basic Search Strategies, Basic Knowledge Representation and Reasoning, Basic Machine Learning, Advanced Search, Advanced Representation and Reasoning, Reasoning Under Uncertainty, Agents, Natural Language Processing, Advanced Machine Learning, Robotics, and Perception and Computer Vision. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 2
Study of theory and/or implementation topics related to information management such as indexing, relational databases, query languages, transaction processing, distributed databases, physical database design, data mining, information storage and retrieval and multimedia systems. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 2
Study of theory and/or implementation topics related to information assurance and security, such as defensive programming, threats and attacks, network security, cryptography, web security, platform security, security policy and governance, digital forensics, and secure software engineering. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 2
Study of theory and/or implementation topics related to computational science such as modeling and simulation, processing, interactive visualization, data, information and knowledge, and numerical analysis. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 2
Study of theory and/or implementation topics related to graphics and visualization such as basic and advanced rendering, geometric modeling, computer animation and visualization. Topics include game programming with concentration on 3D graphics including modeling, rendering, and animation for computer games and graphic simulations. Programs are created using a current graphics and game development environment.Prerequisites: Admission to major or permission.
Credits: 2
Study of theory and/or implementation topics related to human computer interaction such as designing interaction, programming interactive systems, user-centered design and testing, new interactive technologies, collaboration & communication, statistical methods for HCI, human factors and security, design-oriented HCI, and mixed, augmented and virtual reality. This course builds on the use of modern compilers. Related topics covered include lexical scanning, parsing, type checking, code generation and translation, optimization, and compile-time and run-time support for modern programming languages.Prerequisites: Admission to major or permission.
Credits: 2
Study of theory and/or implementation topics related to software engineering such as software processes, project management, requirements engineering, software design, construction, verification and validation, reliability, and formal methods. These relate to advanced programming for general-purpose software development. Topics include tools and processes appropriate for employing object-oriented designs and programming within a significant software development environment and advanced data structures and algorithms, graphical user interfaces, and software development processes.Prerequisites: Admission to major or permission.
Credits: 2
Study of topics theory and/or implementation related to the fundamental differences that Platform-Based Development has over traditional software development addressing topics such as Web Platforms, Mobile Platforms, Industrial Platforms, and Game Platforms. Prerequisite: Admission to Major or PermissionPrerequisites: none
Credits: 4
Students gain experience working with a team to solve a substantial problem in the field of computer science using concepts that span several topic areas in computer science related to cognitive science. Class time focuses primarily on project design and implementation. Senior standing in the Cognitive Science major with a Computer Science Focus.Prerequisites: Senior standing and successful completion of all core requirements.
Credits: 4
The first in a two-semester sequence of capstone design. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Course must be taken concurrently with CS 495.Prerequisites: CS 301, CS 302, CS 303, CS 304, CS 392
Credits: 4
The first in a two-semester sequence of capstone design. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Course must be taken concurrently with CS 495.Prerequisites: CS 301, CS 302, CS 303, CS 304, CS 392W
Credits: 4
The second in a two-semester sequence of capstone design and the fourth project class overall. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Expectations include public presentation of project work, patent applications, and/or plan for commercialization of project. Course must be taken concurrently with CS 495.Prerequisites: CS 491 and (CS 306, CS 401, CS 403, CS 406, CS 410, CS 420, CS 435, CS 440, CS 445, CS 450, CS 465, CS 470, CS 480, or CS 485)
Credits: 4
The second in a two-semester sequence of capstone design and the fourth project class overall. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Expectations include public presentation of project work, patent applications, and/or plan for commercialization of project. Course must be taken concurrently with CS 495.Prerequisites: CS 491W and (CS 306, CS 401, CS 403, CS 406, CS 410, CS 420, CS 435, CS 440, CS 445, CS 450, CS 465, CS 470, CS 480, or CS 485)
Credits: 1-3
Workshop topics will be announced. Workshops on different topics may be taken for credit.Prerequisites: Consent of Instructor
Credits: 1
Students learn about computer science practice through seminars with faculty, graduate students, undergraduate students admitted to the CS major, visiting researchers, and industry members. CS students are assisted in their development as learners and professional citizens through workshops. This course is repeated by upper-division Computer Science students every semester.Prerequisites: Admission to major.
Credits: 1-4
Special topics not covered in other courses. May be repeated for credit on each new topic. VariablePrereq: ConsentPrerequisites: Consent
Credits: 1-6
This course is designed to provide students with an opportunity to utilize their training in a real-world environment. Participants work under the guidance and direction of a full-time staff member. (At most 4 hours towards the CS major.)Prereq: Permanent admission to the CS major, CS 300, consentPrerequisites: Permanent admission to the CS major, CS 300, consent.
Credits: 4
Advanced study and research required. Topic of the senior thesis determined jointly by the student and the faculty advisor.Fall, Spring Prereq: Senior standing and consentPrerequisites: Senior standing and consent
Credits: 1-4
Problems in the field of computer science are studied on an individual basis under the guidance of a faculty mentor.Fall, Spring Prereq: ConsentPrerequisites: Consent
