Overview
This unit explores the statistical modelling methods that underlie the analytic aspects of Data Science and Machine Learning. By working through examples, this unit gives a strong mathematical and statistical foundation to enable a deeper understanding of data analysis and machine learning methods taught in later MDS/MAI units which focus … For more content click the Read More button below.
Offerings
S1-01-CLAYTON-FLEXIBLE
S1-01-MALAYSIA-ON-CAMPUS
S2-01-CLAYTON-FLEXIBLE
Requisites
Prerequisite
Prohibition
Rules
Enrolment Rule
Contacts
Chief Examiner(s)
Dr Zach Swiecki
Dr Levin Kuhlmann
Unit Coordinator(s)
Dr Mohd Fikree Hassan
Notes
Optional Peer Assisted Study Sessions (PASS) run in this unit.
Learning outcomes
On successful completion of this unit, you should be able to:
1.
Perform exploratory data analysis with descriptive statistics on given datasets;
2.
Construct models for inferential statistical analysis;
3.
Produce models for predictive statistical analysis;
4.
Perform fundamental random sampling, simulation and hypothesis testing for required scenarios;
5.
Implement a model for data analysis through programming and scripting;
6.
Interpret results for a variety of models.
Teaching approach
Active learning
Assessment
1 - Assessment 1: Aptitude Activity
2 - Assessment 2: Mid-term test
3 - Assessment 3 - Assignment 1
4 - Final Assessment - Assignment 2
Scheduled and non-scheduled teaching activities
Applied sessions
Seminars
Workload requirements
Workload
Learning resources
Required resources
Recommended resources
Technology resources