Training schedule
IN-COMPANY TRAINING PROGRAMS
Contact Giovanni Lanzani, if you want to know more about custom data & AI training for your teams. He’ll be happy to help you!
Check out more
Experiments the Right Way
Have you ever wondered how Google chooses a color for its home page? How do they decide between two variations? In business, how can you know if changing something will improve it or not?
The two-day A/B Testing and Experiments training will teach you everything you need to successfully run your own experiments.
This training is for you if…
You are a data scientist and you are interested in conducting experiments with statistics
- You are somewhat comfortable with Python & Statistics, and you are interested in understanding more
This training is not for you if…
- You are not comfortable with Python & Statistics and only want the basic concepts. (Check out the Innovation Through Experiments training course instead).
- You would rather deep dive into statistics. (Check out the Bayesian Statistics training instead).
Clients we've helped
What you'll learn
Designing and Running Experiments
- How to design meaningful experiments.
- The intuition behind the statistics needed to make an appropriate decision.
- The practical skills necessary to run your own experiments.
- Common mistakes made in the industry and how to avoid them.
Scaling Up Experimentation
- How to run multiple experiments at the same time
- How long to run an A/B test
- Why stopping early is a bad idea
- How to bootstrap to estimate uncertainties
Improving by Experimenting
- Conduct statistical experiments using Python.
- Avoid common pitfalls that can invalidate your experiments.
- Have confidence that you are making real improvements.
The schedule
- The importance of A/B testing
- How to determine the success of your experiment
- How to design an experiment:
- How to split the population
- How to determine the right metric for your experiment
- Experiment pitfalls and how to avoid them
- Classical hypothesis testing
- Further techniques for conducting A/B tests
- How long to run an A/B test and why early stopping is a bad idea
- Bootstrapping to estimate uncertainties
- Bandit algorithms for real-time A/B testing
After the training you will be able to:
- Conduct statistical experiments using Python.
- Avoid common pitfalls that can invalidate your experiments.
- Confidently make choices that lead to real improvements.
learning journey
Data Science Learning Journey





Rogier van der Geer
Data CharmerBefore joining GoDataDriven, Rogier obtained a PhD in particle physics. Rogier gained hands-on experience with handling enormous quantities of data and processing, or ‘charming,’ them into a manageable format before performing complicated analyses. After his PhD he exchanged physical science for data science at GoDataDriven, where he is now putting his skills to use on more business-driven problems. He likes applying data science to anything; be it his daily commute, improving his photography skills or the contents of his lunch box.
Clients include: Bakkersland, App Annie, Costa Cruises, ING, NPO, Ebay, KLM, and RoyalFlora Holland