COM502: Introduction
COM502: Machine Learning is a centerpiece of the SIAI's MBA AI/BigData (AI/Finance) program, together with COM503: Deep Learning and COM504: Reinforcement Learning.
The course assumes prior knowledge in regression analysis in following courses along with important understanding of key concepts in computational efficiency (discussed in COM501: Scientific Programming)
The course initially covers regression analysis in a sense where traditional linear regression is most powerful. As discussed in earlier math & stat courses, conditional normal distribution on regression is the key for regression being the best linear unbiased estimator (BLUE).
From that point on, the discussion goes to classifiers like logistic regression and move onto graph models such as data grouping, ensembles, together with principal components. In the later part of the course, it covers factor analysis and introduce artificial neural network model as an extension of factor analysis in the context of graph models.
Though final term paper does cover a case example of Machine Learning to a real world application, most extensions are discussed in BUS501: AI in Digital Marketing, a business case course taught in parallel.