The course presents a collection of advanced machine learning topics used in natural language processing and understanding. In particular, it addresses dense vector embeddings, deep learning approaches, ensembles, and visualization of text classifiers. The course covers relevant problems from computational linguistics and text mining, such as word sense disambiguation, detection of multi-word expressions, topic detection, and specifics of morphologically rich languages.  The course is practically oriented and requires students to apply machine learning methods on language processing tasks, preferably in the context of their research work.