Course: Essentials of Predictive Analytics

Event Details

Tuesday October 1, 2019 from 9:00 AM to Tuesday October 8, 2019 5:00 PM
Data Science
€ 1,190.00 ex. vat

Course dates: 1 and 8 October 2019

Predictive analysis using statistics, artificial intelligence and machine learning methods

This course efficiently introduces the essential data science skills needed to develop and use adequate prediction models for quantitative data-based decision making.

On the one hand, the principles of commonly used methods for regression, classification and detection of data clusters are discussed, with special attention to the consequences of big data aspects. On the other hand, practical examples will be used to illustrate how models can be validated, compared and used.

Unique is that during the course participants gain experience in the visual programming of data workflows, with which model-fit, -validation and -comparison can be easily executed in practice.

Using prediction models for decision making

After completion of this course:

  • You have an overview of commonly used methods for predictive modeling from the areas of statistics, artificial intelligence and machine learning.
  • You can develop these models for standard situations independently, using software such as IBM Modeler, SAS-Enterprise Guide and Enterprise Miner or Orange to visually program data workflows.
  • You have gained practical experience with validating, interpreting and comparing alternative models and their use for decision support

Intended for

Professionals who are involved in the analysis of quantitative data and the use of decision support systems, and managers who want to be able to assess and compare the quality of developed models or who control and steer these processes. The course is also suitable for lecturers at universities or colleges of higher education who want to be informed about developments in the field of data science, data mining and data analytics.

In consultation with the participants this course can be taught in Dutch or English.


Data Science

Data Science is an interdisciplinary field that uses a variety of techniques to create value based on extracting knowledge and insights from available data. The successful and responsible application of these methods highly depends on a good understanding of the application domain, taking into account ethics, business models, and human behavior.