Vue d'ensemble
Sciences de la gestion : Introduction to foundational concepts in optimization with a strong emphasis on applications to problems in data science and machine learning, including fundamental optimization models such as linear, integer, and convex programming, a variety of gradient descent methods, and algorithms ( the expectation-maximization and back-propagation algorithm), as well as the applications to various current and diverse data science and machine-learning contexts
Terms: This course is not scheduled for the 2024-2025 academic year.
Instructors: There are no professors associated with this course for the 2024-2025 academic year.
Prerequisites: (INSY 660 or INSY 662) and (MGSC 660 or MGSC 661) or permission of the instructor
Restrictions: Not open to students who have taken MGSC 695 when the topic was "Optimization for Data Science"
1. The online version of the course includes synchronous and/or asynchronous course activities
