ETW2500 - Statistical learning

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Overview

Statistical learning is essential for making sense out of complex data sets and understanding how to implement appropriate modelling and prediction techniques. This unit introduces you to the fundamental concepts of statistical learning and various statistical and machine learning methods in real life settings. You will learn the know-what, know-when, … For more content click the Read More button below.

Statistical learning is essential for making sense out of complex data sets and understanding how to implement appropriate modelling and prediction techniques. This unit introduces you to the fundamental concepts of statistical learning and various statistical and machine learning methods in real life settings. You will learn the know-what, know-when, and know-how of modern business analytics and data science essentials through examples illustrated in the business and economics context. You will also learn to undertake independent analysis using computer software.

Offerings

S1-01-MALAYSIA-ON-CAMPUS

S2-01-MALAYSIA-ON-CAMPUS

Requisites

Prerequisite

Contacts

Chief Examiner(s)

Yalini Easvaralingam

Associate Professor Manjeevan Singh Seera

Learning outcomes

On successful completion of this unit, you should be able to:

understand the concepts of statistical learning

apply appropriate statistical learning concepts and methods to different contextual data

develop technical proficiency in using relevant computer software for empirical analyses

communicate results effectively via oral and written forms.

Teaching approach

Active learning

Problem-based learning

Assessment

1 - Within semester assessment

2 - Examination

Workload requirements

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.