Subject: Interdisciplinary (UG) (IDSC)

CRN: 22971

Online: Asynchronous | Lecture

Online

  Thomas Feeney

The subject matter of these courses will vary from year to year, but will not duplicate existing courses. Descriptions of these courses are available in Classfinder, View Searchable Class Schedule

4 Credits

Subject: Interdisciplinary (UG) (IDSC)

CRN: 22953

Online: Asynchronous | Lecture

Online

  Jonathan Keiser

The subject matter of these courses will vary from year to year, but will not duplicate existing courses. Descriptions of these courses are available in Classfinder, View Searchable Class Schedule

4 Credits

Subject: AI Leadership (Grad) (MAIL)

CRN: 22467

Online: Asynchronous | Lecture

Online

  Thomas Feeney

This course considers the ethics of AI development and deployment. Possible topics include the environmental footprint of AI, data ethics and privacy, intellectual property and training data, algorithmic bias, and AI as a tool for the common good. Further topics may include the global AI divide, autonomous weapons and the militarization of AI, accountability for AI-related harms, impact on vulnerable populations, AI and the transformation of work and society, artificial consciousness and machine rights, and potential catastrophic risks. The course is a roadmap of ethical issues surrounding artificial intelligence.

3 Credits

Subject: AI Leadership (Grad) (MAIL)

CRN: 22290

Online: Asynchronous | Lecture

Online

  Jonathan Keiser

This course provides a focused exploration of current and emerging AI tools, platforms, and ecosystems, equipping students to identify and evaluate their potential applications. Students will gain a practical understanding of diverse AI technologies. Potential examples include machine learning frameworks, natural language processing systems, computer vision applications, and various LLM wrappers. The course will also examine the evolving landscape of AI hardware and software, with a focus on emerging trends and their potential impact on various industries. By the end of the course, students will be able to critically assess AI technologies and make informed decisions about their adoption and implementation.

3 Credits