Enterprise Artificial Intelligence

EAI 6000. Fundamentals of Artificial Intelligence. 3 Hours.

Introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Topics include heuristic search and game trees, knowledge representation using predicate calculus, automated deduction and its applications, problem-solving and planning, and introduction to machine learning. Required coursework includes the creation of working programs that solve problems, reason logically, and/or improve their own performance using techniques presented in the course.

EAI 6010. Applications of Artificial Intelligence. 3 Hours.

Explores numerous industry applications of AI with emphasis on solving specific needs or problems. Applications of AI explored include: Neural Networks, Natural Language Processing, and implications of Cybersecurity. Artificial Intelligence is actively developing in applications across numerous fields and industries, including finance, healthcare, education, and transportation.

EAI 6020. AI System Technologies. 3 Hours.

Presents a selection of systems technologies utilized in AI, including data visualization, file systems for a large data mart, applications of structured query language, and filtering and transforming to ingest data, predictions, etc. Covers mathematics/statistics and computation, machine learning, and privacy requirements.

EAI 6030. Usability and Human Interaction. 3 Hours.

Surveys the theory and practice of human-computer interaction and the development of user interfaces. Through both analysis and design projects, students have an opportunity to learn cutting-edge approaches to usability research and evaluation, testing methods, and how to design systems that meet end-user needs. Topics covered include behavioral and cognitive foundations of interaction design, principles of good design for interaction, basic user research techniques, and the process of user-centered design.

EAI 6050. Finance Information Processing. 3 Hours.

Focusing on the finance industry, provides advanced data management technologies and management systems with emphasis on evaluating the advantages and disadvantages of such technologies in different application contexts. Address specific application contexts of AI and presents the entity relationship to data management (including network hierarchical and object-oriented), with emphasis on processing, storing, and retrieval, while also including privacy requirements.

EAI 6060. Healthcare Information Processing. 3 Hours.

Focusing on the healthcare industry, provides advanced data management technologies and management systems with emphasis on evaluating the advantages and disadvantages of such technologies in different application contexts. As students address a specific application context of AI, this course presents the entity relationship to data management (including network hierarchical and object-oriented), with emphasis on processing, storing, and retrieval, while including privacy requirements.

EAI 6070. Human Resources Information Processing. 3 Hours.

Focusing on human resources, provides advanced data management technologies and management systems with emphasis on evaluating the advantages and disadvantages of such technologies in different application contexts. As students address a specific application context of AI, this course presents the entity relationship to data management (including network hierarchical and object-oriented), with emphasis on processing, storing, and retrieval, while including privacy requirements.

EAI 6080. Advanced Analytical Utilization. 3 Hours.

Focuses on instrumental methods of data analysis and provides a foundation to the theory and application of modern analytical techniques for Artificial Intelligence. Students explore the importance of instrumental analysis for specific uses of AI within various fields and context applications across numerous professional fields.

EAI 6120. AI Communication and Visualization. 3 Hours.

Offers an overview of key informational design concepts, with the emphasis on the relationship between information and audience in the context of communicating complex quantitative information. Encompasses three main context areas: 1. exploratory data visualization, 2. dashboard and scorecard design, and 3. spatial data representation. Discusses ethical questions related to the communication and visualization of data analytics: storytelling, different techniques (such as R-spatial, GeoDa, GeoWave, GeoTrellis, GeoMesa, graph databases network visualization), and principles for visual design, including privacy requirements. .

EAI 6980. Integrated Experiential Capstone. 3 Hours.

The capstone is a multifaceted assignment designed to enable students to apply the knowledge, skills, and best practices acquired throughout the Enterprise Artificial Intelligence program. Students have an opportunity to advance a project plan, conduct research, create and deliver recommendations with the objective to apply artificial intelligence to real-world problems in organizations. Students develop and present the insights and recommendations for successful implementation of the capstone project. Offers a practicum in the development and delivery of discipline‐specific artificial intelligence projects.