2022-2023 Course List

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

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

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:

CIS 518

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:

CIS 518

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.

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.

Content covered will include the following: scientific process; sampling bias; hypothesis tests; confidence intervals; risk analysis vs assessment; statistical analysis concepts. Issues with qualitative and quantitative risk analysis methodologies. Exposure to and practice with multiple risk analysis methodologies, including at least one that is considered a standard.

This course examines the organizational leadership structure and competencies of healthcare and/or IT organizations, the governance planning process, financial management, ethical and legal decision-making, privacy, and data-based best practices that balance organizational and regulatory requirements with feasible cost-effective solutions.

Content covered will include the following: analyze audience; define report outline and objectives for target audience (IT, executives, audit & compliance); ethos/pathos/logos concepts; white papers. Data misrepresentations, intentional or unintentional; appropriate use of data visualization tools and dashboards; representing needle in haystack data (low volume, high risk).

Risk management strategies. Human factors, resistance to change. Design, development and evaluation of security controls; catalog of security controls; performance metrics. Management oversight; cost-benefit analysis, business impact analysis; policies, processes, standards. Technical, administrative, physical controls.

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

Problems on an individual basis. Pre-req: consent

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

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:

CIS 518

A course designed to upgrade the qualifications of persons on-the-job. Pre-req: consent

Student will integrate their health-related background with the practical application of scientific and professional knowledge, behavior, and skills. Students will employ health advocacy strategies, principles of quality improvement, healthcare policy knowledge, and cost-effectiveness as part of an inter-professional team to analyze data and develop a strategy to impact practice improvements in order to increase the quality and efficiency of healthcare delivery, improve satisfaction, or manage health-related costs.

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

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

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

This course offers an introduction to the various disciplines of engineering and their relationship to the principles of physics and mathematics. Students are prepared for academic success and the transition into an engineering program.

Goal Areas:

GE-12

To prepare the students for a career in engineering with some emphasis in civil; introduce the engineering fundamentals and the skills necessary to have a successful learning experience; and to prepare students for engineering education and profession through interactions with upper-class engineering students and practicing engineers.

Prerequisites:

MATH 113 or MATH 115 or MATH 121

Basic computer applications for drafting and designing civil engineering projects. Structure and use of standard CAD software. Basic orthographic construction and projections, and development of different types of drawings - sections, plan and profile, and construction details.

Introduction to the design concepts of civil engineering projects including presentations, codes and standards, construction drawings, and public hearing; problem solving skills for civil engineering analysis and design including the use of appropriate computational tools and programming logic. Includes laboratory component.

Prerequisites:

CIVE 101 

Mechanical behavior and properties of civil engineering materials. Microstructure, response to stress, creep, fatigue, fracture and failure. Composition, application and construction of steel, concrete, asphalt, aggregates, steel, timber, composites and other materials. Includes laboratory component.

Basic civil engineering measurements as relates to construction layout, including distances, angles, bearings, elevations, mapping, and positioning. Includes laboratory component.