In recent years, methods of text analysis based on the paradigm of Distributional Semantics have become hugely popular not only in the Digital Humanities. This workshop will first introduce the participants to the fundamentals of Distributional Semantics as well as to several methods based on this paradigm, particularly Topic Modeling and Word Embeddings. The workshop will then focus on how to practically implement the workflow required to perform Topic Modeling, including data preprocessing, the actual modeling of the data, postprocessing and visualization of results. We will work with several sample datasets, mostly using libraries from the Python programming language. Ultimately, the workshop aims to enable participants to use Topic Modeling to pursue their own research interests and analyze their own collections of textual data.