IAI 5101 Foundations of Machine Learning for Scientists and Engineers
3 units
Interdisciplinary Artificial Intelligence
Faculty of Engineering
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. Recommended prerequisite: No specific programming required, students should have taken an introduction to programming at the undergraduate level as well as linear algebra I & calculus II.
Components:
Lecture
Requirements:
Previously Offered Terms:
Winter