https://at-ceu.studyguide.timeedit.net/modules/DNDS6007?type=COREIn the age of the digital data revolution the collection of human behavioral datasets is a very important issue and requires thorough training for the appropriate design of collection methods. While researchers commonly assume that data is granted at the outset, without control on the data collection pipeline, one never can be sure about intrinsic biases, hidden correlations or unrepresentative sampling. All these can potentially induce misleading noise or undermine any observation/conclusion drawn from the date-driven observations. The aim of this course is to provide proper training on the methodological paths of digital data collection to understand how to translate a scientific hypothesis to data collection pipelines precisely measuring the question in hand with the least possible noise and environmental effects. During the course we will learn in depth about all the latest techniques to collect individual or collective human behavioral data using tracking, monitoring or crawling methods or transactional data technics. We will also learn how to design digital social experiments to collect online surveys or to set up controlled online social experiments. All these methods are in the frontline of computational social science and are pivotal for the coming generation of researchers and data scientists working on any related questions. The course will have a hands-on approach, with homeworks, practical classes and with the development of a project. We will also present methods how students may collect their own social, mobility or health data using their smart phones and readily developed applications. This way they will directly learn all the difficulties and potentials of such technics, while in the end by analyzing their own data would solve any privacy issues during this exercise.