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.
What topics will you cover?
- Running large-scale data mining experiments
- Constructing and executing knowledge flows
- Processing very large datasets
- Analyzing collections of textual documents
- Mining association rules
- Preprocessing data using a range of filters
- Automatic methods of attribute selection
- Clustering data
- Taking account of different decision costs
- Producing learning curves
- Optimizing learning parameters in data mining
When would you like to start?
Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below.
Who is the course for?
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.
Who developed the course?
The 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.
LocationWaikato, New Zealand
World rankingTop 380Source: QS World University Rankings 2021