Practical Data Mining

Learn how to mine data using Weka, with the University of Waikato

On this five-week course, you’ll discover how to mine data using the Weka workbench, a powerful tool for machine learning and data mining.

Guided by experts at the University of Waikato, the original developers of Weko, you’ll learn the basics of data visualisation, classification algorithms, and data interpretation and evaluation.

Explore the basics of data interpretation and evaluation

Beginning with an introduction to data mining concepts, you’ll discover the various applications of data mining in personal and professional contexts.

You’ll examine how to evaluate a classifier’s performance and use training, testing, and cross-validation to gauge the accuracy of the data you’ve gathered.

With these skills, you’ll be able to improve the quality of your data and develop meaningful answers to the questions you’re trying to answer.

Organise your data using classifiers

Exploring both simple and more complex classifiers, you’ll learn how different classification methods can be used to interpret datasets.

You’ll investigate the applications of concepts including decision trees, linear regression, and support vector machines, learning how to apply the correct classification method to your problem.

Examine the full data mining process

In the final week of this course, you’ll put your learning into context by exploring the full data mining process.

You’ll address common pitfalls and challenges to accessing data, as well as assessing the ethics of data mining, giving you a broader understanding of how and when data mining should be used in different contexts.

You’ll finish this course understanding what Weka is and how to gather and interpret big data. You’ll be aware of the full data mining process and be able to explain and apply Weka within your own data mining work.

This course is designed for anyone considering a career in data science or those currently working in the data sector wanting to further their knowledge of data mining software.

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.)

Learn how to process, analyse, and model large data sets

On this course, led by the University of Waikato where Weka originated, you’ll be introduced to advanced data mining techniques and skills.

Following on from their first Data Mining with Weka course, you’ll now be supported to process a dataset with 10 million instances and mine a 250,000-word text dataset.

You’ll analyse a supermarket dataset representing 5000 shopping baskets and learn about filters for preprocessing data, selecting attributes, classification, clustering, association rules, cost-sensitive evaluation.

You’ll also explore learning curves and how to automatically optimize learning parameters.

This course is aimed at anyone who deals in data professionally or is interested in furthering their professional or academic skills in data science.

This course follows on from Data Mining with Weka and it’s recommended that you complete that course first unless you already have a rudimentary knowledge of Weka.

As with the previous course, it involves no computer programming, although you need some experience with using computers for everyday tasks.

High school maths is more than enough; some elementary statistics concepts (means and variances) are assumed.

Before the course starts, download the free Weka software. 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.)