Bayes in Action

Bayesian statistics is making an irreversible global push in all conceivable areas. Despite the simplicity of the formula Bayesian statistics is complex, so complex that it could barely be applied until recently. Thanks to the power of computers and the development of smart algorithms that is past.

for whom

R&D department managers, bio-information researchers, data scientists, econometricians, epidemiologists, pharma scientists, financial managers, forensic investigators, geologists, medical researchers, healthcare managers, market investigators, physicists, space researchers, statisticians, astronomers, meteorologists, and, last but not least, PhD students.

about the course

The basic topics are:
  • what is your model?
  • the ubiquitous Gaussian distribution
  • overfitting the data, which often goes unnoticed
  • regression models, how to optimize the parameters
  • model selection, finding the best model
  • missing data, how to overcome these
  • prediction models and their uncertainty
  • non‐linear models and aliasing

Furthermore, a number of Machine Learning topics discussed, along with their pitfalls! Emphasis is given to practical applications of Bayesian probability theory. Some Wolfram Language will also be demonstrated. A notebook is provided as course material.


A basic mathematical and statistical background is assumed.


Regular courses are held at our office in Amsterdam. Sometimes we provide the courses on site. The location is then mentioned in the agenda below.


3 October 2017, 10.00-17.00 Amsterdam


Standard rate: euro 495+VAT
***Discounted rate: euro 95+VAT for (PhD) students upon request and approval


Dr. Romke Bontekoe

Romke Bontekoe taught himself Bayes in the daily practice. Just by applying Bayes to challenges where standard methods floundered. But where his gut feeling was that there had to be a solution.

He is 60+ years old and he regards it is time to transfer his knowledge and experience to the younger generation. Romke has a doctorate in astronomy from the University of Groningen.

All Mathematica 11 events:
2 October 2017 Deep Learning Applied to Machine Vision Tasks (free) 11.00-16.30 Amsterdam subscribe
3 October 2017 Bayes in Action 10.00-17.00 Amsterdam subscribe
8 November 2017 Mathematica Basic Principles I (free) 10.00-17.00 Amsterdam subscribe
9 November 2017 Mathematica Basic Principles II, includes pattern matching (free) 10.00-17.00 Amsterdam subscribe
15 November 2017 Programming with Mathematica (free) 10.00-17.00 Amsterdam subscribe
22 November 2017 Interactivity in Mathematica
an advanced course for constructing more fine tuned interactive output (free)
10.00-17.00 Amsterdam subscribe