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Description: Modern data collection methods such as EMA/ESM techniques allow us to estimate personalized models. A popular example of such models are time-series networks, capturing dynamic interactions between variables. In this workshop, participants will learn to estimate dynamic networks and to critically reflect on their inferences. In the first part of the workshop, some background on the vector auto-regressive (VAR) model will be provided. The second part will then focus on how the VAR model can be used to construct dynamic networks from EMA/ESM data for both, single subjects as well as multiple subjects. In the third part, we will discuss current challenges to time series modeling and future avenues such as approaches to model continuous processes through differential equations. The workshop will be interactive while relaying key concepts and content. There will be practical exercises using open data, but participants are also able to use their own EMA/ESM data for these practical parts. For this, it is advisable to already do some pre-processing of the data in advance.