Discover practical data mining and learn to mine your own data using the popular Weka workbench.

31,705 enrolled on this course

Data Mining with Weka
  • Duration5 weeks
  • Weekly study3 hours
  • LearnFree
  • Extra BenefitsFrom $84Find out more
This course is part of the Practical Data Mining program, which will enable you to become a data mining expert through three short courses.

Learn how to mine your own data

Today’s world generates more data than ever before! Being able to turn it into useful information is a key skill. This course introduces you to practical data mining using the Weka workbench. We’ll dispel the mystery that surrounds the subject. We’ll explain the principles of popular algorithms. We’ll show you how to use them in practical applications. You’ll get plenty of experience actually mining data during the course, and afterwards you’ll be well equipped to mine your own. Weka originated at the University of Waikato in NZ, and Ian Witten has authored a leading book on data mining.

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Skip to 0 minutes and 4 seconds Hello! My name’s Ian Witten, I’m from the University of Waikato here in New Zealand, and I want to tell you about our new, free, online course – Data Mining with Weka. We’re overwhelmed by data in the world today. Every time we check out an item at the supermarket, every time we swipe our credit card, every time we send an email, every time we type a keystroke on our computer, every time we make a phone call, send a text, walk past a security camera – we all generate a little bit of data.

Skip to 0 minutes and 35 seconds Data mining is about taking this raw data, and transforming it into something more useful: information, perhaps; or predictions, predictions about what might happen next, predictions that can be used in the real world. The real aim of this course is to take the mystery out of data mining, to give you some practical experience actually using the Weka toolkit to do some mining on the data sets that we provide, to set you up so that, later on, you can use Weka to work on your own data sets and do your own data mining. It doesn’t involve any programming or anything like that. You’re going to be using the tools that we provide, the Weka tools.

Skip to 1 minute and 13 seconds It might help to know a little bit of elementary statistics, like means, variances, standard deviations, and so on. You might see a couple of mathematical formulae, but I’ll explain those, so don’t worry about that. You don’t really need any specific mathematical background. So that’s it – Data Mining with Weka, coming soon to a computer near you. I’m looking forward to it, and I hope to see you there. Bye for now!

What topics will you cover?

  • What is data mining?
  • Where can it be applied?
  • How do simple classification algorithms work?
  • What are their strengths and weaknesses?
  • In what ways are real-life classification methods more complex?
  • How should you evaluate a classifier’s performance?
  • What is “overfitting” and how can you combat it?
  • How can ensemble techniques combine the result of different algorithms?
  • What ethical considerations arise when mining data?

When would you like to start?

Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

What will you achieve?

By the end of the course, you‘ll be able to...

  • Demonstrate use of Weka for key data mining tasks
  • Evaluate the performance of a classifier on new, unseen, instances
  • Explain how data miners can unwittingly overestimate the performance of their system
  • Identify learning methods that are based on different flavors of simplicity
  • Apply many different learning methods to a dataset of your choice
  • Interpret the output produced by classification methods
  • Describe the principles behind many modern machine learning methods
  • Compare the decision boundaries produced by different classification algorithms
  • Debate ethical issues raised by mining personal data

Who is the course for?

This course is aimed at anyone who deals in data. It involves no computer programming, although you need some experience with using computers for everyday tasks. High school maths should be more than enough and you’ll need an understanding of some elementary statistics concepts (means and variances).

What software or tools do you need?

You will download the free Weka software during Week 1. It runs on any computer, under Windows, Linux, or Mac. It has been downloaded millions of times and is being used all around the world.

(Note: Depending on your computer and system version, you may need admin access to install Weka.)

Who will you learn with?

I grew up in Ireland, studied at Cambridge, and taught computer science at the Universities of Essex in England and Calgary in Canada before moving to paradise (aka New Zealand) 25 years ago.

Who developed the course?

The University of Waikato

Sitting among the top 3% of universities world-wide, The University of Waikato prepares students to think critically and to show initiative in their learning.

  • Established1964
  • LocationWaikato, New Zealand
  • World rankingTop 380Source: QS World University Rankings 2021

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