Main Menu

Curriculum and Course Descriptions

The Master of Science in Data Analytics and Information Systems has been recommended for approval (with no areas for followup) by the Higher Learning Commission Change Panel, with final approval forthcoming by the HLC’s Institutional Action Council.

Program Requirements………………………………………… 36 Hours

Data Science Requirements…………………………………… 12 Hours
Complete four from the following:

DATA 509 Statistical Analysis (3)
DATA 510 Mathematical Modeling (3)
DATA 512 Operations Research (3)
DATA 518 Big Data Analytics (3)
DATA 599 Special Topis in Data Analysis (3)
BIOL 507 Genomics and Bioinformatics (3)
BIOL 599 Special Topics: Biology (1-4)

Information Systems Requirements…………………………………………………. 12 Hours
Complete four from the following:

IS 580 Introduction to Networking (3)
IS 581 Web Programming (3)
IS 582 Management Information Systems (3)
IS 584 Artificial Intelligence (3)
IS 599 Special Topics in Information Systems (3)

Capstone Requirement…………………………………………………………………….3 Hours
Chose one with Advisor:

DATA 590 Applied Research Project and Capstone (3-6) OR
DATA 591 Internship (3-6)

Elective Courses…………………………………………………………………………….. 9 Hours
Complete three from the following:

IS 583 E-Commerce (3)
IS 585 Information Security (3)
IS 588 Database Management System (3)
IS 599 Special Topics in Information Systems (3)
BIOL 501 Evolution (3)
BIOL 599 Special Topics: Biology (1-4)
DATA 599 Special Topics in Data Analytics (3)

Course Descriptions

 BIOL 501 – Evolution
(3 cr) Evolution processes underpin all biological phenomena and thus represent fundamental and synthetic ideas in all fields. Understanding evolution and how it impacts everything from our health to biotechnology is essential to all scholars. Lecture topics include patterns of macroevolution; mechanisms of microevolution; the nature of adaptation; units and levels of selection; how we measure natural selection; limits to selection; quantitative genetics; the evolution of behavior; and applications of evolution to conservation and medicine. In the laboratory, we will interpret the outcomes of evolution through computation and analysis of phylogenies, genomes, and population genetic structure. Students will be expected to complete an independent research project chosen with guidance from the instructor.

BIOL 507 – Genomics and Bioinformatics
(3 cr) Lectures will introduce some of the common techniques and algorithms used in genomic analysis, including sequence alignment, BLAST, gene expression profiling, and prediction of protein structure and gene function. Throughout the course, we will explore how these techniques, and genomic data in general, have been used to explore topics such as evolutionary history, genetic causes of disease, cancer biology, and ecology (metagenomics). Since genomics is a new and rapidly changing field, we will emphasize topics chosen from recent literature, discussing both the scientific and cultural implications of the work.

The computational lab is an essential component of this course. There is no assumption of previous experience beyond knowing how to move files around and use the web, word processors and spreadsheets. In the first set of labs, students will become comfortable with online databases, sequence alignment, gene expression analysis, and genome-scale data. Students will be expected to complete an independent research project chosen with guidance from the instructor.

IS 580 – Introduction to Networking
(3 cr) This course provides comprehensive coverage in contemporary data communication networking theory as demonstrated by real-world examples with case studies and hands-on projects. The focus is on fundamental principles and concepts of modern local and wide area network such as architecture, design and protocols of TCP/IP networking, the Internet and Web. Also covered are enabling networking technologies for data sciences such as cloud computing and Internet of Things. Students will be expected to complete an independent research project chosen with guidance from the instructor.

IS 581 – Web Programming
(3 cr) This course examines Internet/Web concepts and modern Web programming techniques. Students will develop an understanding of concepts that are essential to developing contemporary Web applications. Web programming languages (HTML, CSS, JavaScript, etc.) and tools are covered with emphasis on client-side Web development. Students will be expected to complete an independent research project chosen with guidance from the instructor.

IS 582 – Management Information Systems
(3 cr) This course provides a comprehensive coverage of modern management information systems in a business setting that involves people, technology and organizations. Topics include structured business information systems, decision support systems, information systems acquisition and management, database management systems, computer and network security, and the role of information processing systems in business decisions. Students will be expected to complete an independent research project chosen with guidance from the instructor.

IS 584 – Introduction to Artificial Intelligence
(3 cr) This course provides an overview of artificial intelligence, its tools and techniques that are essential to data science and data analytics. Topics included are nonprocedural programming, basic search techniques, automated reasoning, and expert systems, with emphasis on the application of artificial intelligence techniques to real-world problems. Students will be expected to complete an independent research project chosen with guidance from the instructor.

Data 509 – Statistical Analysis
(3 cr) This course covers basic statistical skills for advanced work in the functional areas of data science and analytics, including descriptive statistics, probability and its distributions, sampling, and estimation.

Data 510 – Mathematical Modeling
(3 cr) This course is a study of how to model the world around us using mathematics, how to solve the resulting equations, and how to apply the results. It provides a thorough study of how to use both quantitative and qualitative solution behavior in the modeling process. Students will be expected to complete an independent research project chosen with guidance from the instructor.

Data 512 – Operations Research
(3 cr) This course provides an introduction to main topics of operations research: linear programming, network optimization, dynamic programming, and queueing theory. Examples of applications from industry, notably some queueing algorithms, are examined. Additional topics may be chosen from Markov chains, integer programming, nonlinear programming, game theory and decision analysis, and simulation. Students will be expected to complete an independent research project chosen with guidance from the instructor.

DATA 518 – Big Data Analytics
(3cr) This course introduces students to concepts, methods and tools used in the analysis and management of massive data sets. Topics will include the map-reduce programming paradigm, cluster analysis, algorithms and libraries for working with large graphs, disk-based and memory-based distributed computing, stream processing, large-scale machine learning, and analysis of distributed algorithms. The course will explore the historical context, current relevance, and future growth of data analytics. Students will be expected to complete an independent research project chosen with guidance from the instructor.

IS 583 – E-Commerce
(3 cr) This course covers concepts, IT skills and tools, and social and ethical issues encountered performing e-commerce in a contemporary fashion.  Topics include EDI, VAN, ExtraNet, E-Commerce Web development, online shopping cart systems, e-payment, cloud computing, database, and security. Students will be expected to complete an independent research project chosen with guidance from the instructor.

IS 585 – Information Security
(3 cr) Students will be introduced to fundamental concepts of information security including the establishment and implementation of an organization-wide security policy which is designed to protect the information assets of an organization. This course provides the student with the skills necessary to enforce an organization security policy and lays the foundation for continued study in the areas of information security. Students will be expected to complete an independent research project chosen with guidance from the instructor.

IS 588 – Database Management Systems
(3 cr) This course examines the design, implementation and maintenance of a modern database management system. Also covered are database query languages, contemporary database architecture in the Internet and Web based business setting, and security and privacy considerations. Students will be expected to complete an independent research project chosen with guidance from the instructor.

DATA 590 – Applied Research Project and Capstone
(3-6 cr) The student will identify a problem of interest in the area of data science, data analytics or information system, analyze the problem as completely as possible, offer the best alternative(s) for solution, and describe the problem and the proposed solution(s) in a case-study format.

DATA 591 – Internship
(3-6cr) This internship course provides students with the opportunity to apply the cumulative knowledge and skills in the Data Analytics and Information System program to a real-world work environment. The internship involves the following steps: 1) selecting a work site; 2) developing a contract that ensures both employer and student benefit; 3) fulfilling the contract activity through ongoing work; 4) preparing a paper that summarizes the learning experience and outcomes, and 5) presenting the result to the committee. The regular expectation is for a minimum of 150 hours completed in this internship for 3 credits and 300 hours for 6 credits, upon approval by the committee.