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"I really like your product and I can't believe how easy data mining has become and how extendable it is by custom operators."

Marcel Van Velzen, Netherlands

 
Training Seminars

 

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Courses

This page contains information about the courses provided by Rapid-I for data mining, machine learning, knowledge discovery in databases and RapidMiner. We provide these courses for users, decision makers, developers, and administrators. We also provide individual courses here or inhouse at your company or organization. Please contact us for individual arrangements.

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Data Mining and Predictive Analytics: Methods and Applications

Our course "Data Mining and Predictive Analytics: Methods and Applications" is a compact two day introduction into the foundations of data mining and the software RapidMiner. Due to a high number of practical exercises, the participants will be able to transfer the gained knowledge to own data mining problems and solve them quickly and easily.

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Data Mining for Marketing and Sales Optimization

Our course "Data Mining for Marketing and Sales Optimization" demonstrates how data mining can be employed to maximize the gain achieved through marketing. Customer data will be analyized and leads to models describing your customers which can be exploited to better target your marketing activities. This course also describes the practical steps which are necessary to create such models with the software RapidMiner.

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Text Mining with RapidMiner

The course "Text Mining with RapidMiner" is an introduction into knowledge discovery from unstructured data like text documents. It focuses on the necessary preprocessing steps and the most successful methods for automatic text classification (including Naive Bayes and Support Vector Machines, SVM) and text clustering. Many practical exercises for different settings (for example e-mail spam detection, automatical e-mail routing, adaptive personal news filtering, sentiment analysis of text documents like news, web pages, blogs, e-mail, or PDF documents) will enable the participants to transfer the gained knowledge to own text mining problems.

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