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Computer Information ScienceCredits
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.
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.
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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.
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.
This course is designed to give students the skills required to design and develop video games. The primary focus of the course is on mobile game development, game design principles and user-centered design methodologies. A play-centric approach to game design and development will be studied, discussed and applied in the production of a game demo.
Special topics not covered in other courses. May be repeated for credit on each new topic.
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.
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
This course combines theory with hands-on projects in modern computer vision techniques. It covers both foundational and advanced topics, including deep learning, image processing, feature detection and matching, object detection, segmentation, and recognition. The focus is on the practical application of Convolutional Neural Networks and Generative Adversarial Networks in computer vision, while also exploring image generators and addressing the ethical and legal challenges related to synthetic images.
- Prerequisites:
- CIS 631
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
This course explores both the theoretical foundations and practical applications of Natural Language Processing (NLP). Key topics include text processing, language models, sequence-to-sequence models, sentiment analysis, named entity recognition, and machine translation. The course also covers advanced techniques for building and fine-tuning large language models, such as recurrent neural networks, transformers, reinforcement learning, and retrieval-augmented generation. Through hands-on projects and case studies, students will apply their knowledge to build, optimize, and deploy NLP applications, while assessing their ethical implications.
- Prerequisites:
- CIS 631
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
This course prepares students to tackle the ethical, legal, and technical challenges of AI technologies, focusing on issues such as bias, privacy, accuracy, security, and misinformation. Students will explore methods to identify and mitigate bias in AI models, alongside techniques for ensuring data privacy. The course also covers the application of interpretable machine learning and explainable AI techniques and provides a critical examination of data governance frameworks and regulatory guidelines for responsible AI deployment and audits.
- Prerequisites:
- CIS 518
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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.
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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:
- CIS 540
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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.
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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.
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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).
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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.
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
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
- Areas of Interest:
- Health Science | Information Technology | Science, Technology, Engineering, Mathematics
- Programs:
A course designed to upgrade the qualifications of persons on-the-job. Pre-req: consent