This course provides several basic concepts and methods for machine learning. The objective is to familiarize students with some learning algorithms and techniques and their applications. The course introduces different supervised and unsupervised learning methods, parameter estimation techniques, deep learning and reinforcement learning. Publicly available online software libraries and data sets will be used to illustrate the application of these algorithms.

Prerequisites: Computing Science 111 [C- minimum grade required] and Mathematics 115 [C- minimum grade required] and Mathematics 120 [C- minimum grade required] and Mathematics 151 [C- minimum grade required] and 2nd year standing required
Further information: Course availability and times