Welcome to "Statistical Learning" at Dalarna University

Welcome to the "Statistical Learning". It is intended primarily for students taking the Master’s Program in BI and DS.

All of the lessons in this course will be taught at Campus Borlänge. Recorded material will sometimes be made available on our learning platform, and Zoom will be used for digital meetings.

The course covers supervised learning algorithms, with special emphasis on classification methods such as logistic regression, classification trees, linear discriminant analysis, quadratic discriminant analysis, K-nearest neighbour, support vector machine, and regression methods such as linear regression, smoothing splines, generalised additive model, and regression trees. The course also covers unsupervised learning methods such as principal component analysis, k-mean clustering, and hierarchical clustering. Model validation through cross validation, and bootstrap methods are covered. Regularisation for model selection, high dimensional data analysis, and improving prediction performance through model averaging, bagging, and boosting techniques are also covered.
 
We hope you engage in inspiring, interesting, and challenging discussions with your teachers and fellow students. As with all courses at Dalarna University, this course has a strong foundation in theory and research.
An important feature in the design of the course is that it connects theory with practice.

Due to the broad scope of the course, it is impossible to go into depth on all topics, but we hope that what you learn will inspire interest and help you develop the tools you need in your continued professional development.

Here you can find a course handbook CourseHandbook_V1.docx

	Course Syllabus			Contact information
	Reading List			Ilias Thomas Course Coordinator ith@du.se
				Moudud Alam Instuctor maa@du.se
				Raja Omman Jafar Lab assistant roz@du.se