Practical Data Science

€ 2.195 excl. VAT
4 days
In English on request

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

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.”

This course is rated with an average of


Program manager


  • 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

Frequently asked questions

Upcoming dates

Practical Data Science

Startdatum: 13 November 2024
Locatie: Utrecht
Prijs: € 2.195 excl. VAT

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  • "Inzichtvol in de basis (wel/niet verwerpen hypothese), inhoudelijk goed de diepte in (lineaire/logistische regressie) en verbredend met een doorkijk naar verschillende naastgelegen toepassingsvelden. Verder heel veel mogelijke achtergrond als je op een bepaald onderdeel verder zou willen."
    Jos de Greef
    Witteveen+Bos Raadgevende Ingenieurs B.V.
  • "Goede start om R te gaan gebruiken. Je krijgt echt instrumenten in handen om data te analyseren."
    Royal HaskoningDHV
  • "Zeer interessant. Ondanks de moeilijkheidsgraad een goede start om in de praktijk mee door te gaan."
  • "Zeer informatief: goed startpunt voor het gebruiken van R."
    Albemarle Catalysts BV
  • "Erg informatief en toepasbaar."
    Albemarle Catalysts BV
  • "Prima cursus, voldoet aan alle verwachtingen."
    NXP Semiconductors BV Nijmegen

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