This course gives an overview of different learning techniques and algorithms used in Artificial Intelligence (AI). The components involved in building, training, and utilizing AI models will be covered as well as the impact of bias, ethical, and societal issues.
Summer 2026 - Online Fall 2026 - Online Winter 2027 - Online
In this course, students will survey the growing field of Generative Artificial Intelligence, exploring techniques for generating data such as images, text and video using models like generative adversarial networks (GAN), variational auto-encoders, and large language models. The underlying frameworks and algorithms of building cutting-edge generative models will be explored. Offered winter semester. Dual-listed with AI 502.
Summer 2026 - Online Fall 2026 - Online
This course explores the ethical challenges and biases in Artificial Intelligence (AI) systems, focusing on data, algorithmic, and decision biases. Students will examine fairness metrics, bias mitigation strategies, generative Artificial Intelligence biases, and societal impacts, utilizing interdisciplinary approaches to create responsible, equitable artificial intelligence systems. Dual-listed with AI 511. Offered fall and winter semesters. Prerequisite: AI 201.
This course explores artificial intelligence (AI) applications in healthcare and life sciences. Students will learn machine learning, deep learning, medical imaging analysis, clinical text processing, and graph-based bioinformatics. Ethical, regulatory, and privacy challenges in healthcare AI will also be discussed through real-world case studies and hands-on projects. Offered every semester. Dual-listed with AI 588. Prerequisite: CIS 335 or CIS 378, or instructor approval.
Fall 2026 - Online
This course gives an overview of different learning techniques, and algorithms used in Artificial Intelligence (AI). It helps students understand the components involved in building, training, and utilizing AI models. Students will learn about biases, ethical, and societal issues that arise from using AI models for making real-world decisions. Offered fall and winter semesters.
In this course, students will survey the growing field of Generative Artificial Intelligence, exploring techniques for generating data such as images, text and video using models like generative adversarial networks (GAN), variational auto-encoders, and large language models. The underlying frameworks and algorithms of building cutting-edge generative models will be explored. Offered winter semester. Dual-listed with AI 402.
This course explores the ethical challenges and biases in Artificial Intelligence (AI) systems, focusing on data, algorithmic, and decision biases. Students will examine fairness metrics, bias mitigation strategies, generative Artificial Intelligence biases, and societal impacts, utilizing interdisciplinary approaches to create responsible, equitable artificial intelligence systems. Dual-listed with AI 411. Offered fall and winter semesters. Prerequisite: AI 501.
This course explores artificial intelligence (AI) applications in healthcare and life sciences. Students will learn machine learning, deep learning, medical imaging analysis, clinical text processing, and graph-based bioinformatics. Ethical, regulatory, and privacy challenges in healthcare AI will also be discussed through real-world case studies and hands-on projects. Offered every semester. Dual-listed with AI 488. Prerequisite: CIS 635 or CIS 678, or instructor approval.
