luffycullie

I have interest in pursuing a PhD though for financial reasons as an international student I would have to enter the workforce first after masters. Your comments have been really helpful, I think I would go with stochastic processes, time series and 1 or 2 of the linear modeling courses depending on workload constraints.

jjsakurai, thank you for your reply. Pardon my ignorance but from what I've read about neural networks, they mainly use non-linear models. Hence would 2 whole semesters of linear modelling be relevant? I would understand if it is important to ML in general but I'm not sure. Can you also briefly explain how sampling surveys would be useful? That was actually lowest on my list because I thought it was the least related. I am a little biased to the financial modelling applications, but graduate studies (masters) is a priority to me. Thus my draft list was stochastic processes, time series and game theory. Do you think I should trade time series and game theory for the 2 linear modelling courses? Thank you for your time

Hello everyone, I am currently an undergraduate majoring in computer science. I have an option to take 3-4 statistics classes and need some advice regarding which ones would be the most helpful towards graduate research in the areas of machine learning / data-mining. Also if it helps, within ML I'm interested in exploring decision tree learning and neural networks. The list of statistics courses available are: Concepts in Computing with Data Concepts of Probability Concepts of Statistics Stochastic Processes Linear Modelling: Theory and Applications I Linear Modelling: Theory and Applications II Sampling Surveys Introduction to Time Series Game Theory If there are other courses outside of statistics (say in the math department) that you find very relevant, please suggest them too. Thank you!