1. Course overview, a sample text (pre)processing pipeline

2. Quick and dirty intro to ML

3. Distributional semantics, LSA, word embeddings

4. Deep neural networks for NLP

5. Language models and their applications

6. AutoML for NLP

8. Poster session

9. Application example: sentiment analysis

10. Application example: knowledge extraction from text

11. Guest lecture - Knowledge Graph Embeddings for Biodata (Luca Costabello, Accenture Labs)

12. Guest lecture - Use cases in Knowledge Graph extraction (Paul Buitelaar & Ghanshyam Verma, University of Galway)

13. Project presentations