Practical Data Science
During this course you will gain insight into practically useful methods for analyzing and modeling data for predictions and decision-making.
Statistics for big data & business intelligence
As a result of the large scale availability of data nowadays, the use of statistical methods has broadened considerably and the importance and meaning of data science has increased, not only in the laboratory and industry but also in marketing and business intelligence.
For such applications, this course offers essential insights into statistical concepts and skills needed to apply data analysis techniques responsibly. You will learn how to work statistically sound and interpret datasets and models correctly.
The course starts with a review of basic principles from the fields of statistics and probability theory. This provides a good starting point for the data analysis methods within the important fields of data mining (big data) and time series analysis, discussed thereafter. You will also gain experience in working effectively with the statistical software R.
A well-prepared start with data science
The course consists of three topics:
- Applied probability and statistics revisited
intended as a refresher for the principles and techniques that are used within applied probability and statistics for the analysis and modeling of data. - Data mining in a nutshell
provides an introduction and overview of commonly used methods in the field of predictive analytics to generate predictions and classifications based on adequate models and to recognize patterns in large data sets. - Time series analysis in a nutshell
deals with methods for modeling time-dependent data and for making forecasts for the future based on these models.
Intended for
Academics and higher professionals who want to make use of modern applied statistical techniques in their work and who want to familiarize themselves with the relevant skills, and want to get acquainted with the latest statistical freeware. The course is also suited for lecturers at universities or colleges of higher education who want to be informed on actual methods for data analysis and data science.
You have mathematics at at least secondary education level. Basic knowledge in the field of statistics is desirable.
Voorbeelden zijn in R.
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.”
This course 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
Introduction and overview of the course and the software to be used. -
Program day 1
Applied Probability and Statistics Revisited
Module 1:1
• Inleiding en overzicht van de cursus en de te gebruiken software.
• Exploratieve Data Analyse:
• Inleiding kansen, kansrekening en kansverdelingen.
• Oefeningen Exploratieve Data Analys en Kansrekening
- Lunch
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Program day 1
Module 1.2
• Statistical Testing and Estimation in a nutshell.
• Selectie, validatie en gebruik van kansverdelingen in de praktijk.
• Oefeningen Kansverdelingen en Principes van toetsen/schatten
- Closing
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Program day 2
Data Mining in a Nutshell (1)
Module 2.1
• Voorspelmodellen op basis van regressie methoden.
• Selectie, validatie en gebruik van regressie modellen in de praktijk.
• Oefeningen regressie modellen.
- Lunch
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Program day 2
Data Mining in a Nutshell (1)
Module 2.2
• Classificatiemodellen op basis van logistische regressie methoden.
• Selectie, validatie en gebruik van logistische regressie modellen in de praktijk.
• Oefeningen logistische regressie modellen.
- Closing
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Program day 3
Data Mining in a Nutshell (2)
Module 2.3
• Alternatieve methoden voor voorspellen en classificeren.
• Selectie, validatie en gebruik van voorspel en classifciatiemodellen in de praktijk.
- Lunch
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Program day 3
Data Mining in a Nutshell (2)
Module 2.3
• Cluster analyse.
• Oefeningen voorspellen, classificeren en cluster-analyse.
- Closing
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Program day 4
Time Series Analysis in a Nutshell
Module 3.1
• Inleiding, karakterisering en exploratieve analyse van tijdreeksdata.
• Tijdreeksmodellen op basis van Exponential Smoothing.
• Selectie, validatie en gebruik van exponential smoothing modellen in de praktijk.
• Oefeningen exponential smoothing modellen.
- Lunch
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Program day 4
Time Series Analysis in a Nutshell
Module 3.2
• Box-Jenkins modellen voor tijdreeksdata.
• Selectie, validatie en gebruik van Box-Jenkins modellen in de praktijk.
• Oefeningen Box-Jenkins modellen.
- Evaluation and closing
Course leader
dr. Koo Rijpkema
“For me, teaching means sharing knowledge and passion, inspiring and fascinating people through the application of statistics.”
This course 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
- Genoemde prijs is exclusief 21% btw
- Inclusief koffie, thee, lunch en (digitaal) cursusmateriaal
- Prijs is inclusief het volgende verplichte boek:
Frequently 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
Download the Study Guide
Would you like a complete overview of all our courses and trainings? Download the digital study guide!
Upcoming dates
Practical Data Science
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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.