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Microsimulation & Machine Learning with Official Statistics Data
How can we make use of new data sources and data science methods to enhance statistics?
This online course provides an overview of advanced topics in official statistics such as Big Data, machine learning, and microsimulations.
You will gain insight into microsimulation and get an overview of its development and current state-of-the-art microsimulation methods. We will also showcase applications within official statistics.
We will discuss benefits and downsides of using Big Data as a data source for official statistics production and provide examples of its use, including machine learning applications.
You will apply the techniques conveyed in this course in hands-on assignments in R.
Learn online on a flexible schedule
This is an online course. Each week you will..
- watch the weekly videos (~60 min),
- review the assigned readings,
- work on the (R) assignments,
- discuss the material in the weekly online meeting with the instructors from destatis and Statistics Netherlands, and fellow course participants (~60 min).
Online Meetings
Thursday, November 02, 2023, 05:00 PM – 06:00 PM CET
Thursday, November 09, 2023, 05:00 PM – 06:00 PM CET
Thursday, November 16, 2023: NO MEETING
Thursday, November 23, 2023, 05:00 PM – 06:00 PM CET
Thursday, November 30, 2023, 05:00 PM – 06:00 PM CET
Prerequisites
Basic R knowledge is required. You should be able to handle data (data.frames, vectors, lists) using base R and be familiar with the application of functions in general and the generation of graphs. The first two units will make use at least of the packages simPop, laeken, sampling and ggplot2.
About the Instructor
While Hanna Brenzel, who leads the department at the Federal Statistical Office, holds a doctorate in economics, Hariolf Merkle, who has a Master’s degree in survey statistics, is a Data Scientist at the Deutsche Bundesbank. Dr. Marco Puts, on the other hand, is a Methodologist and Lead Data Scientist at the Central Statistics Office in Heerlen and a Guest Researcher at Radboud University in Nijmegen. Piet Daas is a Methodologist and Professor of Big Data in Official Statistics at Eindhoven University of Technology, specializing as a Data Scientist.
Machine Learning Bootcamp in R (€)
Der Machine Learning Bootcamp in R vermittelt in einzeln buchbaren Modulen elementare Methoden und Konzepte zur Anpassung und Optimierung von Vorhersagemodellen aus dem Bereich Predictive Modeling und Supervised Machine Learning (Modul 1), zum Auffinden von Strukturen in den Daten aus dem Bereich des Unsupervised Machine Learning (Modul 2), sowie praktisches Wissen zum interpretierbaren maschinellen Lernen (Modul 3). Beschreibung der Module:
Modul 1: Supervised Machine Learning in R(06.03. – 08.03.2023)
Modul 2: Unsupervised Learning in R(09.03.2023)
Modul 3: Interpretable Machine Learning in R(10.03.2023)
How to Make Use of Machine Learning & Microsimulation in Official Statistics
How can we make use of new data sources and data science methods to enhance public statistics?
This course gives an overview of advanced topics in official statistics such as Big Data, machine learning, and microsimulations. The benefits and downsides of using Big Data as a data source for official statistics production are discussed and examples of its use are given, including machine learning applications.
In addition, the course provides insights into microsimulation and gives an overview of the past, the present, and the future state-of-the-art of microsimulation methods and applications within official statistics.
This online course uses a flipped classroom design, which means that you can watch the weekly hour of video lectures according to your own schedule. In the weekly one-hour online meetings you have the chance to discuss the material and hands-on applications with the instructors from destatis and Statistics Netherlands.
Basic R knowledge is required. Having some familiarity with the official statistics system as taught in Walter Radermacher’s BERD Academy workshop series “Statistics for the Public Good” can be helpful.
About the Instructors
While Hanna Brenzel, who leads the department at the Federal Statistical Office, holds a doctorate in economics, Hariolf Merkle, who has a Master’s degree in survey statistics, is a Data Scientist at the Deutsche Bundesbank. Dr. Marco Puts, on the other hand, is a Methodologist and Lead Data Scientist at the Central Statistics Office in Heerlen and a Guest Researcher at Radboud University in Nijmegen. Piet Daas is a Methodologist and Professor of Big Data in Official Statistics at Eindhoven University of Technology, specializing as a Data Scientist.