Essentials of predictive analytics

€ 1.395 excl. VAT
2 days
Course
In English on request

Acquire essential data science skills needed to develop and use adequate predictive models for decision-making based on quantitative data and learn how to use generative AI, such as ChatGPT or Copilot, in this process in a responsible way.

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.

Furthermore, possibilities and dangers of using generative AI, such as ChatGPT and Copilot, when applying AI and machine learning methods in practice will be explicitly addressed and demonstrated.

Using prediction models for decision making

At the end of this module you will:

  • 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.

Would you like to have more background information or read about experiences of data analysis course participants? Read our interviews:
Interview with Hendrik-Jan de Kort (SPIE Nederland). He and his team followed an incompany data training to build on AI-knowledge.
Interview with Tomaso della Vedova and Chantal Visser (Endress + Hauser), about their incompany course on data mining and predictive modeling.
Course leader dr. Koo Rijpkema (University of Technology Eindhoven) shares his vision on the world of data and courses and the importance of the discipline.

In English on request

Do you want to follow the course in English? Please mention this in the remarks field when you register.

Course leader

Data analysis and programming

dr. Koo Rijpkema

Eindhoven University of Technology (TU/e)

“For me, teaching means sharing knowledge and passion, inspiring and fascinating people through the application of statistics.”

PAOTM is rated with an average of

8,3

Program manager

Why PAOTM

  • The latest post-academic knowledge and skills
  • Focused on questions that arise in a technical environment
  • Interactive and directly applicable in practice
  • Top teachers from science, research and business

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Upcoming dates

Essentials of predictive analytics

Startdatum: 5 February 2025
Locatie: Utrecht
Prijs: € 1.395 excl. VAT
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