Intelligence artificielle interdisciplinaire (IAI)

IAI 5100 Foundations and Applications of Machine Learning (3 units)

The capabilities and limitations of machine learning; problem formulation; supervised and unsupervised learning techniques; deploying, monitoring, and evaluating machine learning models; storytelling and assessing the results of learning; current advances in application areas such as business, law, arts, social sciences and education. The courses IAI 5101, CSI 4145, CSI 5155 and ELG 5255 cannot be combined for units.

Course Component: Lecture

Recommended prerequisite : An aptitude for analytics. Although no specific programming background is required, students should be comfortable with computing technologies.

IAI 5101 Foundations of Machine Learning for Scientists and Engineers (3 units)

The capabilities and limitations of machine learning; problem formulation and requirement engineering; supervised and unsupervised learning techniques; designing, deploying, monitoring and evaluating machine learning models; assessing the results of learning; current advances in application areas such as engineering, science and health. The courses IAI 5100, CSI 4145, CSI 5155, ELG 5255 cannot be combined for units.

Course Component: Lecture

Recommended prerequisite : Students should have completed courses on linear algebra I and calculus II. Although no specific programming background is required, students should have taken an introductory programming course at the undergraduate level.

IAI 5120 Essential Concepts in Data Science (3 units)

An introduction to the foundations of data science using a case study approach; overview of the data science process: types of tasks and models, data manipulation, exploratory data analysis, data summarization and data visualization; predictive modeling, descriptive modeling; reporting and deployment. The courses CSI 4142, DTI 5125, DTI 5126, MAT 4373 cannot be combined for units.

Course Component: Lecture

Recommended prerequisite : It is recommended to have completed a course on statistics and probability. Although no specific programming background is required, students should be comfortable with computing technologies.

IAI 5130 Ethical, Societal and Legal Aspects of Artificial Intelligence (3 units)

The interplay between Artificial Intelligence, society, the law, and ethics; the course will explore how advances in Artificial Intelligence affect the law and other social institutions, and, conversely, how societal, legal, and ethical considerations affect the development and deployment of Artificial Intelligence technologies. The courses CSI 5195, DTI 5310, ELG5295 cannot be combined for units.

Course Component: Lecture

Recommended prerequisite: Although no specific programming background is required, students should have courses or practical experience to be comfortable with computing technologies.

Retour au sommet