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University of Waikato launches MOOC on data mining

University of Waikato launches MOOC on data mining

The first MOOC (massive open online course) from a New Zealand university was launched by the University of Waikato this week in one of the most exciting fields of contemporary computer science – data mining.

For the University of Waikato’s Department of Computer Science, the choice of Data Mining with Weka for a MOOC was an obvious one - students around the world are already familiar with the software and have written and uploaded tutorials on YouTube.

“The open source Weka software was developed here at the University, and it’s been downloaded over half a million times,” says University of Waikato Professor Ian Witten. “A lot of people around the world use it, so it makes sense that data mining with Weka is the topic of our first MOOC.”

Through this MOOC, the University of Waikato is making available the expert knowledge of its researchers and teaching staff in a structured online environment. Extracts from the book Data Mining: Practical Machine Learning Tools and Techniques – co-authored by Professor Witten and now in its third edition – will be made available within the course and students who pass two tests will receive a statement of completion.

A series of videos simply and clearly explain how the course will work, what students will need to complete it and what they will get at the end of it.

“Some people are talking about monetising MOOCs by selling diplomas, advertising, and suchlike, but we're not thinking about any of those things at the moment,” says Professor Witten, who was recently recognised with a University of Waikato lifetime achievement research award. “For us, this is all about learning, both for students to learn about data mining and to give our own staff experience and knowledge of MOOCs.”

Data mining –also known as machine learning – has enormous potential as more and more of daily life is conducted online, generating vast amounts of information. Until recently, analysing that data in a way that was useful and relevant has been beyond most people’s capability.

But not anymore. With the rise of software such as Weka (Waikato Environment for Knowledge Analysis), huge quantities of raw data can be sifted and analysed, extracting information on every aspect of life, from traffic flows on city streets to which restaurants people are eating at. The Weka workbench, an organised collection of state-of-the-art machine learning algorithms and data preprocessing tools, has been used in a wide number of applications. It has helped determine what information dairy farmers use in deciding which cows to keep in their herd and to analyse milk production.


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