The University of Waikato Department of Computer Science
- Start Date: 06 Mar, 2017
- 5 weeks
- Study Content: Videos
Discover practical data mining and learn to mine your own data using the popular Weka workbench.
Course Fee: Free
Certificate Cost: See Fees and Eligibility
Course Description
This course is made available through the eLearnAfrica and FutureLearn partnership.
In a world that generates more data than ever before, being able to turn data into useful information is critical. That’s where data mining comes in. On this course you’ll get an introduction practical data mining using the Weka workbench. We’ll dispel the mystery that surrounds data mining and explain the basic principles of several popular algorithms and how to use them in practical applications. After completing the course will be able to mine your own data.
Learn how to use the Weka workbench
We’ll start by looking at what data mining is and where it can be applied. You will download and install the popular open-source Weka workbench on your own computer and discover how to use it to run many common classification algorithms, including:
- decision trees
- decision rules
- nearest neighbor
- Bayesian methods
- linear and nonlinear regression
- classification by regression
- logistic regression
- support vector machines
- the “maximum margin hyperplane”
We’ll also look several ensemble techniques – and study the principles behind these various methods, including how different ones produce different shapes of classification boundary.
Discover how to evaluate data mining results
You will find out how to reliably evaluate the result of your learning, including baseline accuracy, cross-validation, and overfitting; along with many related pitfalls. You will learn about various techniques of data filtering, and how to apply them. You’ll also discover how to visualize your data within Weka.
Explore the overall data mining process using a variety of datasets
Through the course you’ll develop an awareness of the overall data mining process including the pitfalls, and ethical issues concerning the use of data mining.
You’ll get to explore datasets from various walks of life, with prescribed experiments for you to analyse them – as diverse as diabetes, CPU performance, attributes of glass, breast cancer, labor relations, soybeans, schizophrenia, even flowers – and slugs.
By the end of the course you should realise there’s no magic in data mining, although it might seem that way!
Certificate cost may vary. You will be redirected to the host page for cost and payment options.
The University of Waikato Department of Computer Science
This University is committed to delivering a world-class education and research portfolio, providing a full and dynamic university experience, distinctive in character, and pursuing strong international links to advance knowledge.
This institution is available on eLearnAfrica through partnership with FutureLearn.
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