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Gain the big data analytics skills that are in demand today

Big data is a fast-growing field and skills in the area are some of the most in demand today.

The Big Data Analytics program from Queensland University of Technology (QUT) comprises four online courses that each look at a different element of big data.

You’ll begin by examining how big data is collected and stored, before going on to explore how statistical inference, machine learning, mathematical modelling and data visualisation are used in its analysis.

You’ll become familiar with predictive analysis, dimension reduction, machine learning, clustering techniques and decision trees, before going on to look at the maths that underpins many of the tools you can use to manage and analyse big data.

Accessible for free on desktop, tablet or mobile and delivered in bite-sized chunks, the courses provide a flexible way to develop your big data analytics skills.

When you complete all four courses and buy a Certificate of Achievement for each, you will earn a FutureLearn Award as proof of completing the program of study.

Courses

Complete 90% of each course and score an average of 70% or above on any tests within it, to be eligible to buy a Certificate of Achievement for it. Complete all courses and buy all Certificates, to receive a FutureLearn Award.

This program will require 8 weeks of learning and cost a total of £176.00 + shipping.

Learn with big data experts and world-leading researchers

The Big Data Analytics program has been developed by the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) at Queensland University of Technology (QUT), which brings together for the first time a critical mass of Australia’s best researchers in mathematics, statistics and machine learning.

Learning outcomes

The Big Data Analytics program is open to anyone with an interest in big data and is essential if you’re looking to add big data analytics to your skill set.

By the end of the program, you will be able to:

  • identify big data application areas;
  • use big data frameworks;
  • model and analyse data by applying selected techniques;
  • demonstrate an integrated approach to big data;
  • and participate effectively in a team working with big data experts.