Enhance your skills in practical data mining as you get to grips with using large data sets and advanced data mining techniques.
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.)