Essentials of predictive analytics
You will acquire essential data science skills needed to develop and use adequate predictive models for decision-making based on quantitative data.
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
dr. Koo Rijpkema
“For me, teaching means sharing knowledge and passion, inspiring and fascinating people through the application of statistics.”
PAOTM is rated with an average of
Program manager
Why PAOTM
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The latest post-academic knowledge and skills
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Focused on questions that arise in a technical environment
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Interactive and directly applicable in practice
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Top teachers from science, research and business
Frequently asked questions
Program
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Introduction to course, software, and case-study.
• Principles in predictive analytics:
- Data pre-processing, data exploration & data
reduction.
- Over-fitting and model tuning.
• Resampling methods & regularization
- Lunch
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Essentials of prediction modeling
- Overview of commonly used prediction methods, such as linear regression, neural networks, regression trees and nearest neighbor algorithms.
• Selection, validation, and use of predictive models in practice
- Completion day 1
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Essentials of classification
- Overview of commonly used classification methods, such as logistic regression, neural networks, classification trees, support vector machines and nearest neighbor algorithms.
• Selection, validation, and use of classification models in practice.
- Lunch
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Essentials of cluster and segmentation models.
- Overview of commonly used cluster and segmentation methods, such as hierarchical, k-Means and Louvain clustering.
- Selection, validation and use of cluster and segmentation models in practice.
• Epilogue: review, trends, and next steps.
- Completion day 2
Course leader
dr. Koo Rijpkema
“For me, teaching means sharing knowledge and passion, inspiring and fascinating people through the application of statistics.”
PAOTM is rated with an average of
Frequently asked questions
Dates and locations
Below you will find an overview of the available dates and locations. You can register immediately by clicking on the 'Register' button.
Investment
- Price excludes 21% VAT
- Including coffee, tea, lunches and (digital) course material
Need a quotation?
Heb je vooraf een offerte nodig voor jouw cursusaanvraag? Vraag deze hier eenvoudig aan.
Request a quotationFrequently asked questions
In-company
Are several employees interested in the same course, do you want to enrich knowledge with the entire team or focus on your own practice? Then an in-company course could be interesting. We are happy to think along with you about the possibilities. PAOTM has extensive experience in organizing in-company courses in many technical fields for a wide range of companies. You can choose to have an existing course organized in-company for multiple employees. However, if you have a specific organizational or departmental issue, we can also design a unique course. For every customized request, we search our network at universities, knowledge institutes and the business community for the right teachers who can provide your team with the desired knowledge. We then put together a course based on your training needs, learning needs and organizational goals.
Curious about the possibilities? Contact one of our program managers or complete the form below. We are happy to make you a suitable offer.
FAQ's
In-company request
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Program manager
In-company courses of PAOTM are rated with an average of
Why In-company
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A course tailored to your specific needs
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Get started right away with your own cases
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Led by top teachers with the most up-to-date knowledge
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You choose where and when: always efficient
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The entire team trained simultaneously
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Customization possible in all our fields
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Upcoming dates
Essentials of predictive analytics
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Download the Study Guide
In addition to the course offerings, the Study Guide also contains the themes that we will further develop next year. Would you like a complete overview of our courses and training in your field(s)? Request the Study Guide and receive it digitally.
