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.

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 course develops essential AI literacy skills for students entering the modern workforce. Students learn to effectively use AI tools, engineer prompts, evaluate AI outputs, and understand ethical implications of AI in professional settings. Through industry-informed case studies and hands-on projects, students develop competencies in data analysis, digital skills, complex cognitive tasks, decision-making, and continuous learning with AI assistance. PW: Digital Literacy Pract

This course explores the intersection of artificial intelligence (AI) and cybersecurity, focusing on how AI and machine learning can be used to solve cybersecurity problems and how adversaries exploit AI vulnerabilities. The course covers advanced topics such as Cyber Threat Intelligence (CTI), malware analysis, and classification, and students apply techniques learned to real-world datasets.

This course introduces the foundations and central characteristics of artificial intelligence (AI) with a focus on how generative AI systems learn and how understanding those learning mechanisms can improve the ways we as humans engage with AI.

This course explores AI adoption across business and nonprofit sectors, focusing on AI-driven decision-making, workflow automation, and business intelligence applications. Through case studies and readings, students will assess strategic AI integration, ethical risks, and the competitive advantage of AI-powered business strategies.