• Fully Funded

Discover practical data mining and learn to mine your own data using the popular Weka workbench. This course is part of the Practical Data Mining program, which will enable you to become a data mining expert through three short courses.

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. They’ll dispel the mystery that surrounds the subject. They’ll explain the principles of popular algorithms. They’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.

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).

The course has been designed by 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.

The University of Waikato is a consistent climber in the most prestigious international rankings. They’ve risen 127 places in the QS World University Rankings in five years, and the latest Times Higher Education World University Rankings brought them up to third equal in New Zealand.

Academic staff at Waikato are passionate about their area of expertise and are committed to helping students to build the skills and knowledge they will require to be successful in their careers. Students are encouraged to engage with academics, including asking questions and generating debate during lectures.




  • The course is free. However, there is an option to upgrade the course which would include the a certificate and some extra capabilities.
  • By the end of the course, participants will be able to:
    • Demonstrate use of Weka for key data mining tasks.
    • Explain how data miners can unwittingly overestimate the performance of their system.
    • Apply many different learning methods to a dataset of your choice.
    • Describe the principles behind many modern machine learning methods.
    • Debate ethical issues raised by mining personal data.
    • Evaluate the performance of a classifier on new, unseen, instances.
    • Identify learning methods that are based on different flavors of simplicity.
    • Interpret the output produced by classification methods.
    • Compare the decision boundaries produced by different classification algorithms.


Applicants need to know high school maths with knowledge of elementary statistics.

Eligible Regions: Open for All

Application Process

Please visit the official website for the application process.

Apply nowOfficial link

For Further Queries

Please visit the official website for any enquiries.
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