Courses

This course explores the rapid adoption of generative AI tools in business, that have helped streamline business processes and decision-making. With a focus on AI applications for marketing, management, finance, statistics, and professional development, this course will provide students with the necessary knowledge and skills to navigate the applications and ethical considerations related to AI. Students will recognize the potential of AI for responsible business growth.

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 provides an in-depth introduction to the principles and techniques used in artificial intelligence (AI). It covers both foundational and advanced principles underlying AI. It explains the differences between AI, machine learning, and deep learning. It explores critical topics such as neural networks, natural language processing, reinforcement learning, and robotics. Students will gain experience with generative AI tools and prompt engineering.

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.

This course explores the integration of artificial intelligence (AI) and machine learning (ML) into modern industrial robotics and automation systems. Focusing on practical applications within the industry 4.0 paradigm, students will study robot kinematics, smart sensing, programmable logic controllers (PLCs), machine vision, collaborative robotics (cobots), and AI-driven control and communication frameworks through simulations, hardware labs, and project-based learning.

This course explores the transformative potential of Generative Artificial Intelligence (GenAI) in education, equipping learners with the skills to critically assess and apply AI tools to address real-world challenges. Through hands-on practice, learners will develop prompt engineering techniques, create AI-powered instructional solutions, and address key issues such as equity, ethics, and accessibility.

This course introduces students to artificial intelligence in investment management. Students apply tools such as natural language processing, forecasting, and workflow automation to analyze financial data, evaluate corporate performance, and manage a real-money portfolio, with emphasis on ethical evaluation and strategic decision- making in asset management and fintech.

This course provides an in-depth introduction to artificial intelligence (AI) in interactive simulation and game development, focusing on practical implementation using Unreal Engine 5's Blueprint system. Students will explore core AI concepts, historical developments, and hands-on techniques to create intelligent interactive simulation system and game behaviors. The curriculum includes interactive activities, mini projects for each module, and a collaborative team project spanning the semester.