Overview
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Academic contacts
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Offerings
KAPLAN-SGP-TJA-MIXEDMODE-2025-2025
KAPLAN-SGP-TMA-INT-2024-2024
KAPLAN-SGP-TMA-MIXEDMODE-2026-2026
KAPLAN-SGP-TSA-MIXEDMODE-2025-2025
MURDOCH-S2-EXT-2023-2024
MURDOCH-S2-FACE2FACE-2025-ONGOING
MURDOCH-S2-INT-2023-2024
MURDOCH-S2-ONLINEFLEX-2025-ONGOING
Enrolment rules
Enrolment in an IT graduate course or M1330 Master of Engineering Practice or M1289 MBA /MIT Master of Business Administration / Master of Information Technology or permission of the Academic Chair.
Other learning activities
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Learning activities
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Learning outcomes
1.
Demonstrate and apply a practical and theoretical understanding of the terminology, principles, fundamental tools and techniques of data analysis.
2.
Plan data modelling and design activities, use statistical learning methods at the correct level of detail for meeting assigned business objectives.
3.
Demonstrate the applicability of modern, powerful predictive models to different domains. Support business intelligence needs through using data science. Select techniques based on a breadth of knowledge of the strengths, weaknesses and expected performance of different approaches.
4.
Specify and apply appropriate data science techniques through specialised programming languages.
Assessments
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Additional information
Unit content:· The Data Science Process
· Definition and Concepts of Statistical Learning
· Data Pre-processing
· Machine Learning Algorithms
· Over-Fitting and Model Tuning
· Linear and Non-Linear Regression
· Measuring Performance in Regression Models
· Basic Classification Models
· Factors that can affect model performance
· Recommendation Engines: How do they work
· Social Networks Analysis: You and your Twitter followers
· Introduction to R
Other notes:Each student is expected to spend on average three hours per teaching week reading the lecture notes, books chapters and other recommended materials relevant to the topic covered in that week and spend a similar amount of time working on the workshop exercises for that week. In addition, each student is required to complete two assignments and sit the final examination.