Statistical Foundations for Data Science and Artificial Intelligence

Postgraduate | 2026

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Area/Catalogue
STAT 5011
Course ID icon
Course ID
204966
Level of study
Level of study
Postgraduate
Unit value icon
Unit value
6
Course level icon
Course level
1
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No
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Note:
Course data is interim and subject to change

Course overview

The aim of this course is to introduce students to the foundational statistical methods and data analysis techniques essential for understanding and applying key concepts in data science and artificial intelligence. Through this course, students will learn to apply statistical models, visualise data, and interpret results within the context of introductory real-world applications in AI and data science. 

Course learning outcomes

  • Explain key statistical concepts, including data types, uncertainty, and the role of scientific inquiry in data science and AI
  • Apply exploratory data analysis techniques to summarise and visualise datasets, identifying key patterns and relationships
  • Perform basic probability calculations and statistical inferences, including constructing and interpreting confidence intervals and hypothesis tests
  • Implement data transformation techniques to improve data quality, address non-normality, and enhance model performance
  • Build, interpret, and evaluate linear regression models for prediction and decision-making, addressing common issues such as multicollinearity and heteroscedasticity

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A