Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Queensland University of Technology

Big Data: Mathematical Modelling

Queensland University of Technology via FutureLearn

This course may be unavailable.


Learn how mathematics underpins big data analysis and develop your skills.

Mathematics is everywhere, and with the rise of big data it becomes a useful tool when extracting information and analysing large datasets. We begin by explaining how maths underpins many of the tools that are used to manage and analyse big data. We show how very different applied problems can have common mathematical aims, and therefore can be addressed using similar mathematical tools. We then introduce three such tools, based on a linear algebra framework: eigenvalues and eigenvectors for ranking; graph Laplacian for clustering; and singular value decomposition for data compression.

This course is designed for anyone looking to add mathematical methods for data analytics to their skill set. We provide a multi-layered approach, so you can learn about the methods even if you don’t have a strong maths background, but we provide further information for those with a sound knowledge of undergraduate mathematics. We will assume basic MATLAB (or other) programming skills for some of the practical exercises.

MathWorks will provide you with free access to MATLAB Online for the duration of the course so you can complete the programming exercises. Please visit MATLAB Online to ensure your system meets the minimum requirements.

Taught by

Tomasz Bednarz, Ian Turner and Kerrie Mengersen


4.0 rating, based on 1 Class Central review

Start your review of Big Data: Mathematical Modelling

  • Profile image for Sonsoles López
    Sonsoles López

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.