|Lecture hours per week||2|
|Lab hours per week||2|
In this course, students will be introduced to supervised learning techniques and algorithms. Coursework includes linear regression, logistic regression, decision trees, bayesian learning, support vector machines, sequence learning, and ensemble techniques. The concepts of under-fitting, overfitting, cross-validation, and kernel methods will be covered throughout the course.