Course: Data Mining & Business Analytics

Fundamental concepts for understanding and successfully applying data mining methods (with R)

It is becoming increasingly easy and common to collect and store large amounts of data. This applies for example to consumer data, data on individual behavior, warranty and fault data and production processes where sensors log data on a large scale.
With the help of data mining it is possible to discover relationships and structures in such large amounts of data and to develop prediction models. Techniques from applied statistics, artificial intelligence and machine learning are used.
In this course you will learn fundamental concepts for understanding and applying data mining methods. Using practical examples and exercises you will gain experience with data mining software, such as R, Minitab, JMP or IBM-SPSS.

Successful application of data mining methods

During this course:

• You will learn the most common techniques in the field of applied statistics, artificial intelligence and machine learning that are important for understanding and successfully applying data mining methods.
• Gain insight and skill in the basic techniques needed to perform analyses with relevant software in the field of data mining.

Intended for

Academics and higher professionals who are dealing in their work with data mining issues and the analysis of large data files. The course is also suitable for lecturers from universities and colleges of higher education who want to become acquainted with current methods in the field of data mining. Background in a specific discipline is not required. Knowledge of basic statistical techniques such as testing, estimation and regression modelling is desirable. In consultation with the participants this course can be taught in Dutch or English.