Covers the basics of Natural Language Processing, including tokenization, part-of-speech tagging, and embeddings, and explores practical applications like sentiment analysis.
Delves into Deep Learning for Natural Language Processing, exploring Neural Word Embeddings, Recurrent Neural Networks, and Attentive Neural Modeling with Transformers.
Introduces the course on information systems, covering its structure, objectives, and foundational concepts essential for understanding data management and decision-making.
