This course provides a technical perspective on NLP - methods for building computer software that understands and manipulates human language. Contemporary data-driven approaches are emphasized, focusing on machine learning techniques. The covered applications vary in complexity, including for example Entity Recognition, Argument Mining, or Emotion Analysis. Through lectures, exercises, and a final project, you will gain a thorough introduction to cutting-edge research in NLP, from the linguistic basis of computational language methods to recent advances in deep learning and large language models.
Large Language Models (LLMs), such as GPT-3, BERT, and their successors, have had an enormous impact on various domains, including natural language processing, machine learning, and artificial intelligence. These models have redefined what’s possible in applications like text generation, translation, summarization, sentiment analysis, and more. The aim of this seminar is to explore the cutting-edge research, insights, and trends in the field of LLMs.