Course Outline


  • Overview of Weka
  • Understanding the data mining process

Getting Started

  • Installing and configuring Weka
  • Understanding the Weka UI
  • Setting up the environment and project
  • Exploring the Weka workbench
  • Loading and Exploring the dataset

Implementing Regression Models

  • Understanding the different regression models
  • Processing and saving processed data
  • Evaluating a model using cross-validation
  • Serializing and visualizing a decision tree model

Implementing Classification Models

  • Understanding feature selection and data processing
  • Building and evaluating classification models
  • Building and visualizing a decision tree model
  • Encoding text data in numeric form
  • Performing classification on text data

Implementing Clustering Models

  • Understanding K-means clustering
  • Normalizing and visualizing data
  • Performing K-means clustering
  • Performing hierarchical clustering
  • Performing EM clustering

Deploying a Weka Model


Summary and Next Steps


  • Basic knowledge of data mining process and techniques


  • Data Analysts
  • Data Scientists
  14 Hours


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