Courses

This course is a practical and theoretical study of Artificial Intelligence and Gaming consoles. Topics include the collection and analysis of artificial intelligence and the use of artificial intelligence to enhance the analysis of digital evidence. This framework investigates smart home devices or forensic investigations of Autonomous Vehicles and logs. Also, collecting and analyzing game consoles and the use of consoles by bad actors.

Students apply AI and Machine Learning (ML) principles and algorithms to develop through the entire analysis, design, implementation, testing, and delivery lifecycle. components of the project, test, prepare deliverable documents, and present the project.

This course provides an in-depth exploration of fundamental machine learning concepts and techniques, including supervised, unsupervised, and semi-supervised learning, alongside practical applications of these concepts in real-world problems. It further delves into the intricate world of deep learning, investigating critical topics such as deep neural networks, convolutional neural networks, and recurrent neural networks, as well as recent advancements in the field.

This course introduces students to the fundamental principles of sound design for video games, covering sound effects, background music, and interactive audio techniques. Students will explore how sound enhances player immersion and emotional impact, learning practical methods for recording, editing, and designing game audio. The course emphasizes both traditional and AI-assisted sound design, introducing tools for music composition, procedural sound generation, and adaptive audio techniques.

Techniques for the accelerated development of better and more robust software using emerging artificial intelligence (AI) tools such as OpenAI Codex, IntelliCode and others. Covers AI assisted key software development stages from requirements gathering, designing, coding, code review, debugging, testing and deployment to maintenance.

This course explores AI-powered automation in business, covering chatbots, workflow optimization, and decision support. Students apply low-code AI tools, prompting, and automation strategies to enhance efficiency. Ethical and security implications are examined, preparing students to implement AI-driven solutions in evolving business environments.

Exploration and development of emerging AI technologies and a small team project identifying a problem for an external client organization, or a specific internal research project, to plan, execute, and complete an application of AI to address the problem or research question. Students will deliver the completed algorithm and supporting documentation to the client or researcher.

This course provides a comprehensive foundation in the mathematical concepts and techniques essential for understanding and developing artificial intelligence algorithms. Emphasizing both theoretical principles and practical applications, key areas including linear algebra, calculus, probability, and statistics will be explored.

This interdisciplinary course addresses the medical, epidemiological, and psychosocial issues surrounding the AIDS epidemic. It places the epidemic within a social, political and policy context, examining the impact of the AIDS epidemic upon the U.S. urban setting, including a specific analysis of the medical, public health, legal, and housing institutions.

Students examine the intensity and magnitude of health problems due to HIV progression, and the management of AIDS. The course focuses on prevention addresses the economical, sociological, and ethical issues of AIDS.