R - Datamining

There are lots of tools that do Data Mining. But few of them can compete with R in terms of flexibility. This 3-day training gives you all you need for your first Data-Mining-Project with R.

Beginning with basic Data-Mining-workflows in R, you will get an good overview of the most important packages and tools for R. Multiple interactive exercises and real-world demonstrations will help you to internalize the basic steps of Data Mining: data exploration and management.

The second part of the training focuses on the most important methods for the analysis of Big Data. This includes clustering methods (K-Means, Hierarchical Clustering) and prediction models (Decision Trees, Neural Networks, Random Forests). You will learn how to apply, interpet and use these models using efficient R-implementations.

Content

• Data Mining Workflow (SEMMA)
• Explorative Data Analysis and Data Management for Big Data in R
• Unsupervised Learning: Clustering
• Supervised Learning: Prediction Models
  • Decision and Regression Trees
  • Artifical Neural Networks
  • The concept of Ensemble Models and Random Forests

Requirements

Students should have a basic idea of how to work with R. This would be covered in our training Explorative Data Analysis with R.