Utrecht, Netherlands

Data Science: Data Analysis

when 20 July 2021 - 24 July 2021
language English
duration 1 week
credits 1.5 EC
fee EUR 700

Due to the covid-19 outbreak, this course has been postponed to 2021.

The course Data science: Data Analysis offers a range of statistical techniques and algorithms from statistics, machine learning and data mining to make predict future events and uncover hidden structures in data. The course has a strong practical focus; participants actively learn how to apply these techniques to real data and how to interpret their results. The course covers both classical and modern topics in data analysis.

What puts former criminals on the right track? How can we prevent heart disease? Can Twitter predict election outcomes? What does a violent brain look like? How many social classes does 21st century society have? Are hospitals spending too much on health care, or too little?

Statistical learning is the art and science of tackling questions like these by analyzing data. Just as cartographers make maps to see what a country looks like, data analysts make graphics that reveal hidden structures in the data. And just as doctors diagnose sick patients and advise healthy ones on how to stay healthy, data analysts predict the consequences of actions and/or events so we can act on that knowledge. Methods from statistics, data mining, and machine learning play an important part in this process.

The course has a strong practical character; the focus is not on the mathematics behind the methods but on the principles that make them work. Participants learn how to apply these methods to real data and how to interpret the results. The course covers both classical and modern topics in data analysis.

Course leader

Dr. Maarten Cruyff

Target group

Applied researchers and master students from applied fields such as sociology, psychology, education, political science, public policy, quantitative criminology, human development, marketing, management, biology, medicine, computational linguistics, communication sciences. A maximum of 60 participants will be allowed in this course. Please note that the selection for this course will be done on a first-come-first-served basis.

Course aim

This course aims to provide you with hands-on experience applying classical as well as modern statistical learning techniques, using R.

Fee info

EUR 700: Course + course materials
EUR 200: Housing fee (optional)

Register for this course
on course website