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University of Waikato launches MOOC
Fri, 23rd Aug 2013
FYI, this story is more than a year old

The first Massive Open Online Course (MOOC) to come out of a New Zealand university has been launched by the University of Waikato this week in one of the most exciting fields of contemporary computer science – data mining.

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

Ian Witten, University of Waikato professor, says the open source Weka software was developed at the University, and has been downloaded over half a million times.

“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. 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 Witten. “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, 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 Data Mining with Weka MOOC can be found at: http://weka.waikato.ac.nz