This course is an introductory course designed to provide undergraduate students with a foundation in understanding artificial intelligence (AI) and its role in society. The course explores the history, principles, and applications of AI, as well as ethical considerations tied to its growth and integration into various sectors. Students will gain practical skills in evaluating AI-powered systems and engaging with AI in their daily lives.

This course invites students to explore the hype and potential of AI through guided experimentation, critical reflection, and practical application. Students will engage in hands-on activities, rhetorical analysis, and ethical inquiry to develop applied AI literacy while learning about human-in-the-loop frameworks for ethical AI use, the principles and techniques of prompt engineering, and the broader impacts of AI on privacy, intellectual property, and user experience. Throughout the course, students will experiment with AI tools in academic, professional, and personal contexts, cultivating the skills and critical awareness needed to use these technologies effectively and responsibly.

What AI is, and what it may become, are in part functions of the cultural context in which it has been developed. In this course, we will investigate the cultural, historical, and mythological roots of Artificial Intelligence—from ancient Greek automata to the computer age. From this starting point, we will grapple with the shifting ethical and political aspects of AI in the world today. Readings and activities draw on anthropological and ethnographic studies of science, technology, and society. No prerequisites.

This course will examine representations of artificial intelligence in international and U.S. narrative cinema from 1980s to present. The course will argue that film representations of artificial intelligence demonstrate that ethical and moral quandaries surrounding the AI have been occupying the public imaginaries for year. The course will ask how these representations of artificial intelligence have dealt with uncertainties of technologies, including, but not limited to, human extinction, technological advances, and robotic and cyborg entities. We will argue that science fiction cinema and its representations of AI are singularly important to an understanding of contemporary cultural anxieties.

This course provides an introductory yet application-driven exploration of Geospatial Artificial Intelligence (GeoAI), focusing on how spatial data is integrated with AI-driven techniques to address real-world geographic challenges. Students will learn to preprocess, analyze, and visualize geospatial datasets while using AI tools such as machine learning (ML) and deep learning (DL). Instead of requiring extensive programming knowledge, the course will introduce AI through user-friendly, block-based programming tools (e.g., JupyterLab Blockly) alongside structured Python-based exercises. By the end of the course, students will be able to apply AI-powered geospatial methods to practical problems in areas such as urban planning, environmental monitoring, and remote sensing. Through interactive labs, discussions, and a capstone project, students will develop both the technical skills and conceptual understanding needed to apply AI in geospatial science.

This artificial intelligence course will prepare students to become a skillful big data handler and user for assisting teams dealing with big data analytics, visualization and decision making in corporate, educational, government organizations. In addition to learning AI prompting and AI-assisted coding, students will have ample opportunities to make decisions to allocate about $500,000 of real financial resources through individual and team projects. Students will also get an opportunity to present their course project at several inter-university competitions with a chance to shine at national platforms.

Provides an introductory overview of artificial intelligence in education, addressing foundations and applications of artificial intelligence in education, the role of learning design, critical issues, and associated areas of research.

Understand artificial and natural phenomena in fields like biology, psychology, neuroscience, economics, and engineering through computational concepts and practices.

Exploration of how AI as a thought partner can enhance the three primary functions of effective leaders –setting strategy, making effective decisions, and aligning people and actions with organizational goals. Students will be exposed to best practices in each of these domains, and then gain practical experience using AI as a thought partner to be more effective in each.

While Artificial Intelligence (AI) began in the 1950s, recent work in Generative AI has taken the world by storm, creating the possibility for both great advancement and great harm. This course serves both as an Introduction to Artificial Intelligence (and its roots in philosophy) as well as Ethical issues AI presents. This course will give students a working knowledge of the different kinds of AI and what they can do, the relationship between natural and artificial intelligence, and the ethical issues in using AI that any user or producer of the technology should know (whether you are just trying to keep yourself safe, avoid being fooled, or interested in reducing a company’s risk associated with AI).

This course explores the transformative impact of AI technologies on society and health, emphasizing their potential to revolutionize healthcare delivery and outcomes. The course is divided into three sections. The first section introduces the fundamentals of AI, including its history, ethical and societal considerations, and applications in health. The second section focuses on hands-on programming exercises, incorporating tools like R studio and ChatGPT to simulate healthcare scenarios and analyze real-world applications with simple machine learning algorithms. In the final section, students will synthesize their learning by presenting ideas on the interplay between AI, society, and health. Course materials include primary literature, case studies, and multimedia resources, while practical components feature interactive programming assignments and exercises with R studio, ChatGPT and other AI tools, fostering a critical and applied understanding of AI’s impact on health and society.

Study of language-based generative AI and its intersection with language learning. Introduction to fundamentals of artificial intelligence (AI), tracing its origins and distinguishing between types of AI. Exploration of the basics of language learning, understanding how human languages work and how they are learned. Training in using chatbots and related apps responsibly and ethically for academic learning.