Studyportals
Short Course Online

Data Mining with Weka

FutureLearn

35 days
Duration
Free
Free
Unknown
Tuition fee
Unknown
Unknown
Apply date
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Start date

About

Discover practical data mining and learn to mine your own data using the popular Weka workbench with the Data Mining with Weka course from The University of Waikato by FutureLearn.

Overview

Today’s world generates more data than ever before! Being able to turn it into useful information is a key skill. This Data Mining with Weka course from The University of Waikato by FutureLearn 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

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

Programme Structure

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?

Key information

Duration

  • Part-time
    • 35 days

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced
  • No Attendance
  • Proactive tutoring and support
  • Individual work/assignments (with online group discussions)

Academic requirements

We are not aware of any academic requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • 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).

Tuition Fee

To alway see correct tuition fees
  • International

    Free
    Tuition Fee
    Based on the tuition of 0 USD per year during 35 days.
  • National

    Free
    Tuition Fee
    Based on the tuition of 0 USD per year during 35 days.

It's free to join and study this course, you have the option to upgrade  and receive a digital and printed certificate for $79. Additional benefits can be reached via the Unlimited FutureLearn product. 

Funding

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Fresh content

Updated in the last 9 months

Check the official programme website for potential updates.

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Data Mining with Weka
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