Handbook

Data science and machine learning represent an overlap of statistics, computer science and domain expertise. The combination of statistics and computer science, allows machine learning methodology to take advantage of the strengths of both areas yielding methods that have some advantages over statistical analysis and computational algorithms on their own.

A broad understanding of data science and machine learning methods  enables  one to interpret correctly and make decisions from research using common supervised and unsupervised methods such as linear and logistic regression, classification and regression trees, neural networks, support vector machines and clustering.

Note:  Students who have completed INFO411 prior to studying STAT351 will not receive credit for STAT351.  Students who complete STAT351 first may continue on to complete INFO411 and receive credit for both.