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Rsch Sch of Finance, Actuarial Studies & App Stats · ANU College of Business and Economics
Statistical Learning is a course designed for students who need to carry out statistical analysis, or “learning”, from real data. Emphasis will be placed on the development of statistical concepts and statistical computing. The content will be motivated by problem-solving in many diverse areas of application. This course will cover a range of topics in statistical learning including linear and non-linear regression, classification techniques, resampling methods (e.g., the bootstrap), regularisation methods, tree based methods and unsupervised learning techniques (e.g. principle components analysis and clustering).
Typical assessment may include, but is not restricted to: exams, assignments, quizzes, presentations and other assessment as appropriate
Learning outcomes 1, 2, 3, 4, 5, 6, 7
Students are expected to commit at least 10 hours per week to completing the work in this course. This will include at least 3 contact hours per week and up to 7 hours of private study time.
Information about the prescribed textbook will be available via the Class Summary.