Overview
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Academic contacts
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Offerings
DUBAI-ISC-TJD-INT-2023-ONGOING
DUBAI-ISC-TSD-INT-2023-ONGOING
KAPLAN-SGP-TJA-INT-2023-2023
KAPLAN-SGP-TMA-INT-2022-2022
KAPLAN-SGP-TMA-INT-2024-2024
KAPLAN-SGP-TSA-INT-2021-2021
KAPLAN-SGP-TSA-INT-2023-2023
MURDOCH-S1-INT-2018-2019
MURDOCH-S2-EXT-2022-ONGOING
MURDOCH-S2-INT-2020-ONGOING
Enrolment rules
Enrolment in an IT graduate course or permission of the Academic Chair.
Other learning activities
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Learning activities
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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.