UO Mathematics Essentials in Data Analytics

Undergraduate | 2026

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Area/Catalogue
MATH 1034
Course ID icon
Course ID
204153
Level of study
Level of study
Undergraduate
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.
Yes
Discipline group A
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
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Note:
Course data is interim and subject to change

Course overview

The aim of this course is to provide students with working knowledge of mathematical and statistical concepts relevant to applications in data analytics. The aim of this course is topics covered in this course include: linear algebra concepts, vectors and matrices operations, eigenvalues and eigenvectors, dynamical systems, optimisation techniques (e.g. Gradient descent), linear regression, probability concepts (probability laws, Bayes' rule and independence), selected probability distributions, statistical inference and applications to data analytics.

Course learning outcomes

  • Demonstrate working knowledge of linear algebra, including vectors and matrices to solving problems.
  • Apply selected optimisation techniques in the context of data analytics.
  • Apply probability concepts and statistical methods to solving data analytical problems.
  • Communicate results of mathematical modelling in context of data analytics.

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A

Assessment

Problem Solving Task, Assignment

Degree list
The following degrees include this course
Bachelor of Data Analytics
Associate Degree in Data Analytics