Location: AG/ET Building, Room 116, 903-886-5321
Dr. Andrea Graham, Dean
The College of Science & Engineering offers graduate degree programs in: Artificial Intelligence, Biological Sciences, Chemistry, Computer Science, Mathematics, Physics, and Technology Management.
Government and private studies project occupations requiring a Science, Technology, Engineering, and Mathematics (STEM) degree, or related skills, to continue to be in high demand and will make up a significant portion of the U.S. and global economy. The College of Science & Engineering boasts recognized and award winning faculty and state-of-the-art research facilities/equipment. As a graduate student, there are unique opportunities to work with faculty in fields such as biomedical, image processing and recognition, data mining, alternative energy, catalyst development, high performance computing, cybersecurity, skin lesion algorithms, differential geometry spatial algorithms, nuclear astrophysics, surface physics, observational astronomy, STEM education, or other STEM research fields. We are strongly committed to professional development, STEM teacher preparation, and preparing individuals to succeed in terminal degree programs.
AI 500 - Foundations of Artificial Intelligence
Hours: 4
This course is a general introductory course designed to accommodate students with diverse majors. It serves as an entry point into the world of artificial intelligence (AI) by providing a strong foundation in essential science principles, including algorithms, data structures, and problem solving. Natural language processing is the other core field of AI, connecting human language generation and understanding as key intelligent behaviors. Throughout this course, students will apply various algorithms using fundamental data structures, such as lists, trees, and graphs to solve various AI problems. By the conclusion of this course, students will possess a robust knowledge base, equipping them to engage with AI in various contexts, from research to practical application. Embark on this intellectually stimulating journey to uncover the core principles driving the AI revolution, tailored to the diverse academic backgrounds of graduate students. Prerequisites: CSCI 513.
AI 510 - Seminar in Artificial Intelligence Ethics
Hours: 3
As artificial intelligence (AI) continues to transform various aspects of our lives, it becomes imperative to examine the ethical implications of its development, deployment, and impact on society. This course is a topical seminar is a topical seminar designed to engage students in critical discussions surrounding the ethical challenges and dilemmas posed by AI technologies. Topics may vary, but may include: bias and fairness; transparency and accountability; AI and social justice, legal implications, emerging technologies, case studies, privacy issues, ethical guidelines and policy development. Prerequisites: CSCI 513 or CSCI 515.
AI 520 - Machine Learning for Artificial Intelligence
Hours: 3
This course is a foundational course designed to introduce students into the interdisciplinary applications of Artificial Intelligence, focusing on the robust field of Machine Learning. The course will look at computer algorithms that automatically acquire new knowledge and improve their own performance through experience. This comprehensive, application-oriented course is the first step in the AI master's program, specially tailored to accommodate students from a variety of academic disciplines including computer vision, natural language processing, and decision making in healthcare and finance. Topics include linear and logistic regression, artificial neural networks, Bayesian networks and learning, decision trees, kernel / support-vector machines, statistical learning methods, unsupervised learning, reinforcement learning, and other currently emerging algorithms. Prerequisites: CSCI 513.
AI 595 - Research Literature and Techniques
Hours: 3
A course designed to acquaint the student with the role of research in the initiation, development and modification of concepts and theories in computer science. A final written report and presentation and/or demonstration of results obtained during the course will be made to interested faculty members and students.
