Information Technology (MS)

Summary

Thesis Plan – 32 credits
Alternate Plan Paper – 34 credits
Coursework Plan – 36 credits

Catalog Year

2019-2020

Degree

Master of Science

Total Credits

32

Locations

Mankato

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Program Requirements

Research/Methods Course(s)

Research methodology in general and in computer science. Data and research sources. Analysis of existing research. Preliminary planning and proposals. Conceptualization, design, and interpretation of research. Good reporting. Same as CS 600. Pre-req: An elementary statistics course.

Prerequisites: none

Restricted Electives

Choose 10 Credit(s).

Students attend seminar presentations and present a research topic at one of the seminars. Same as CS 602. Pre-req: consent

Prerequisites: none

In-depth study of advanced topics such as object-oriented databases, intelligent database systems, parallel databases, database mining and warehousing, distributed database design and query processing, multi-database integration and interoperability, and multilevel secure systems.

Prerequisites: none

In this course, students will design and implement distributed big data architecture. The architecture consists integration of homogenous and heterogeneous databases and other structured and unstructured data sources. Students will apply concepts of distributed recovery and optimization, and other related topics.

Prerequisites: none

This course will focus on research, design, and analysis of computer networks and data communications systems. The course will also entail detailed examination of modern communication standards, protocol systems and their implementation. Additional topics may include transmission technology, packet switching, routing, flow control, and protocols. Same as CS 662. Pre-req: IT 562 or 564

Prerequisites: none

Advanced software design, analysis, and development techniques under realistic time and budget constraints. Hands-on project management techniques. Emphasis of concepts through immersion in a team project of significant size. Same as CS 680. Pre-req: IT 580

Prerequisites: none

Specialization - Choose a minimum of 8 credits from any one of the following groups:

Database Technologies

Extensive coverage of SQL, database programming, large scale data modeling, and database enhancement through reverse engineering. This course also covers theoretical concepts of query processing, and optimization, basic understanding of concurrency control and recovery, and database security and integrity in centralized/distributed environments. Team-oriented projects in a heterogeneous client server environment.

Prerequisites: none

This course provides science and study of methods of protecting data, and designing disaster recovery strategy. Secure database design, data integrity, secure architectures, secure transaction processing, information flow controls, inference controls, and auditing. Security models for relational and object-oriented databases. Pre: With permission by instructor.

Prerequisites: none

The course explores big data in structured and unstructured data sources. Emphasis is placed on big data strategies, techniques and evaluation methods. Various data analytics are covered. Students experiment with big data through big data analytics, data mining, and data warehousing tools.

Prerequisites: none

HTTP Protocol; Presentation abstractions; Web-markup languages; Client-side programming; Server-side programming; Web services; Web servers; Emerging technologies; Security; Standards & Standard Bodies; Techniques for web interface design; User-centered design; Visual development environments and development tools; Measure the effectiveness of interface design. Pre: With permission by the instructor.

Prerequisites: none

Networking and Information Security

Extensive coverage of SQL, database programming, large scale data modeling, and database enhancement through reverse engineering. This course also covers theoretical concepts of query processing, and optimization, basic understanding of concurrency control and recovery, and database security and integrity in centralized/distributed environments. Team-oriented projects in a heterogeneous client server environment.

Prerequisites: none

This course provides science and study of methods of protecting data, and designing disaster recovery strategy. Secure database design, data integrity, secure architectures, secure transaction processing, information flow controls, inference controls, and auditing. Security models for relational and object-oriented databases. Pre: With permission by instructor.

Prerequisites: none

Advanced coverage of data communication, networking and security protocols. Topics include: data transmission methods, error detection and recovery, flow control, routing, data throughput, security issues, and performance analysis of existing and emerging protocols for secure communication between the many points within a computer network and across the internet. Pre: With permission by the instructor.

Prerequisites: none

Network and server systems administration include: domain administration; file system management; networked printers; user management; and workstation configuration. Network programming experience will be gained through programming assignments/projects in Layered Software Systems, HTTP Server, UDP (TFTP or DNS), CGI program, IPV6, RPC/SCTP. Pre: With permission by the instructor.

Prerequisites: none

This course provides an understanding of existing and emerging mobile and wireless data networks, with an emphasis on digital data communications. Students will gain an understanding of the unique considerations that must be given to network protocols for wireless and mobile communication as well as their applications. Pre: With permission by the instructor.

Prerequisites: none

HTTP Protocol; Presentation abstractions; Web-markup languages; Client-side programming; Server-side programming; Web services; Web servers; Emerging technologies; Security; Standards & Standard Bodies; Techniques for web interface design; User-centered design; Visual development environments and development tools; Measure the effectiveness of interface design. Pre: With permission by the instructor.

Prerequisites: none

Software Development

This course endeavors to provide the student with a solid understanding of the principles, techniques and tools involved in advanced object-oriented programming as it is practiced in enterprise industries. The successful student should have a distinct advantage in the marketplace. Pre: With permission by the instructor.

Prerequisites: none

Topics include software quality assurance, software quality metrics, software configuration management, software verification and validation, reviews, inspections, and software process improvement models, functional and structural testing models.

Prerequisites: none

This course discusses concepts and techniques for design, development and evaluation of user interfaces. Students will learn the principles of interaction design, interaction styles, user-centered design, usability evaluation, input/output devices, design and analysis of controlled experiments and principles of perception and cognition used in building efficient and effective interfaces. Group project work.

Prerequisites: none

HTTP Protocol; Presentation abstractions; Web-markup languages; Client-side programming; Server-side programming; Web services; Web servers; Emerging technologies; Security; Standards & Standard Bodies; Techniques for web interface design; User-centered design; Visual development environments and development tools; Measure the effectiveness of interface design. Pre: With permission by the instructor.

Prerequisites: none

An introduction to all important aspects of software engineering. The emphasis is on principles of software engineering including project planning, requirements gathering, size and cost estimation, analysis, design, coding, testing, implementation, and maintenance. Group project work.

Prerequisites: none

Unrestricted Electives

Broad Electives - Choose credits in any combination from the following or above to satisfy the total credit requirement for the Information Technology MS.

600–level courses from the following list:

Special topics in computer science research not covered in other courses. May be repeated for credit on each new topic.

Prerequisites: none

This course is a continuation of Artificial Intelligence (IT 530). Emphasis is placed on advanced topics and the major areas of current research within the field. Theoretical and practical issues involved with developing large-scale systems are covered. Same as CS 630. Pre-req: IT 530

Prerequisites: none

The design of large-scale, knowledge¿based data mining. Emphasis on concepts and application of machine learning using big data. Examination of knowledge representation techniques and problem¿solving methods used to design knowledge¿based systems. Pre-req: instructor permission required

Prerequisites: none

Problems on an individual basis. Pre-req: consent

Prerequisites: none

Statistical package programs used in data collection, transformation, organization, summarization, interpretation and reporting, statistical description and hypothesis testing with statistical inference. Interpreting outputs, Chi-square, correlation, regression, analysis of variance, nonparametrics, and other designs. Accessing and using large files (U.S.Census data, National Health Survey, etc.). Same as CS 690. Pre-req: a statistics course

Prerequisites: none

Any other 500–level courses from the Department of Information Systems & Technology.
Up to 8 credits of 5/600-level nondepartmental courses in consultation with the advisor (Max. 4 credits at 500-level from nondepartmental sources)

Capstone Course

Choose one option

Provides students with opportunity to utilize their training in a real-world business environment working under the guidance and direction of a faculty member. (A maximum of 4 credits apply toward a degree in this department.) Pre: consent Fall, Spring, Summer

Prerequisites: none

Preparation of a master's degree alternate plan paper under the direction of the student's graduate advisor. Pre-req: consent

Prerequisites: none

Preparation of a master's degree thesis under the direction of the student's graduate advisor. Pre-req: consent

Prerequisites: none