Training - Data Mining

With growing amounts of data we need new methods for data analysis. This three-day-class gives an overview over the most important datamining-methods. Unsupervised learning methods try to find structures in your data without an explicit response variable. Typical unsupervised methods are principal component- and cluster-analysis. The main topic in this class are prediction models. This includes logistic regression, decision trees and neural networks. The class concludes with the general idea of ensemble-prediction-models.

Content:

• Uses cases in data mining
• Clustering (KMEANS, Hierarchical clustering)
• Principal component analysis (PCA)
• Prediction modeling (logistic regression, decision trees, neural networks)
• Concept of ensemble-models

Requirements:

None

Duration of the training: 3 days