Extend your repertoire of data mining scenarios and techniques
This course will bring you to the wizard level of skill in data mining, following on from Data Mining with Weka and More Data Mining with Weka, by showing how to use popular packages that extend Weka’s functionality. You’ll learn about forecasting time series and mining data streams. You’ll connect up the popular R statistical package and learn how to use its extensive visualisation and preprocessing functions from Weka. You’ll script Weka in Python – all from within the friendly Weka interface. And you’ll learn how to distribute data mining jobs over several computers using Apache SPARK.
What topics will you cover?
- Time series analysis
- Data stream mining
- Incremental classifiers
- Evolving data streams
- Support vector machines
- Accessing data mining in R
- Distributed data mining
- Map-reduce framework
- Scripting data mining in Python and Groovy
- Applications: Soil analysis, Sentiment analysis, Bioinformatics, MRI neuroimaging, Image classification
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. You should have completed Data Mining with Weka and More Data Mining with Weka – or be an experienced Weka user. Although the course includes some scripting with Python, you need no prior knowledge of the language. You will have to install and configure some software components; we provide full instructions.
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