City of Amsterdam employees empowered for data driven working with Xomnia Academy training

We designed a customized, four-part, quarterly training program to help the Municipality of Amsterdam become more data-driven and have its employees gain more data awareness. The knowledge obtained throughout the training program can help the city address social challenges and opportunities.

Xomnia gave a customized training to improve daily work activities. Our new and expanded data science skills can be used to organize internal processes and improve municipal services. The potential impact is far-reaching
- The Municipality of Amsterdam


The Municipality of Amsterdam has a goal of becoming more data driven throughout its departments. The objective is to utilize data science to enhance services for citizens, work more efficiently, and address social challenges. However, it was difficult to realize data science possibilities across the vast array of services, organizational levels, and procedures present in the Municipality.


The Municipality turned to Xomnia’s Academy training for customized courses to support the Municipality employees throughout the phases of their data driven journey. Xomnia designed a four part program, from entry to expert level, targeted at guiding participants through stages ranging from data awareness all the way to taking the first steps in machine learning.  

The Data Driven Working program courses are:

  1. Introduction: Data Science
  2. First Aid for Data Analysis
  3. Data and Data Modeling
  4. Data Analysis: Next Level

The City of Amsterdam offers the training program to all employees through their continuing education platform. Xomnia delivers each training course every quarter in the year. The program design enables participants to choose their own pace to build their data capabilities.

By the end of the first course, participants know what data science is and how it is applied in daily practice. They are able to oversee the cycle of a data science project and determine the correct approach. Introduction: Data Science provides an understanding of the possibilities and challenges in working with data. Participants also get hands-on experience using RapidMiner, a visual data mining tool, by building their own predictive model.

The second course, led by an experienced data analyst, provides hands-on experience with different data types, such as numeric, text, and geo data. Participants of First Aid for Data Analysis use data visualization tools and learn how to quickly move from a data source to an analysis. They work with Excel and Tableau for the practical exercises, get experience with data sources accessible via an API, and build a dashboard.

Subsequently, the Data and Data Modeling course focuses on dealing with data from a variety of sources. Employees of the Municipality of Amsterdam are particularly faced with this challenge in their day-to-day activities at the municipality. This training teaches how to estimate the value present in the data which is derived from different sources. By the end of the course, participants will be able to structure the data and convert it to a model.

The last component of the program is targeted at experienced data analysts who would like to advance into data science. The Data Analysis: Next Level course teaches the basics of machine learning. They will learn the different types of models and when to apply them. Participants will put their knowledge into practice by programming in Python. At the end of the training, they will be able to train machine learning models and apply them in their work.


The knowledge gained throughout the training program can help the Municipality address social challenges effectively and creatively. Employees can also use their new and expanded data science skills to organize their department’s internal processes and improve municipal services. The potential impact is far-reaching.

When a municipality empowers its employees to approach challenges and opportunities with a data-driven mindset, it not only benefits the municipality but also the residents themselves. We are happy to contribute to this advancement within our own home city,
- Lisanne Rijnveld, Xomnia data scientist and Academy training lead