The University of Cyprus's course on Natural Language Processing is part of the Master programmes in Artificial Intelligence 4 Careers in Europe (MAI4CAREU). One of Master's programme's courses is split up into several lectures and is taught by Demetris Paschalides from the Department of Computer Science, whose research interest is focused on the use of Natural Language Processing (NLP) and Machine Learning (ML) to address social and ethical challenges. 

Learning outcomes 

This lecture on ‘Fundamental Text Pre-Processing’ follows a first short introductory lecture into the course. The lecture looks at:

• Regular Expressions (RegEx) and their role in NLP
• Word tokenisation, word normalisation and sentence segmentation 
• Text similarity as a key component of NLP 
• Types of text similarity (including: morphological similarity, spelling similarity, synonyms, and semantic similarity)
• Minimum Edit Distance (MED) and its fundamental role in NLP

The lecture illustrates the theory with a lot of practical examples, illustrations, and interactive diagrams to offer students a comprehensive understanding of the course material. The instructor also provides a list of resources for further learning.

Course outline

The Natural Language Processing course is divided into 7 subsections: 

1. Text Pre-processing
2. Language Modeling
3. Text Classification
4. Word Vector Representation
5. Distributed Contextual Embeddings
6. Application of NLP in:
   1. Hate-speech Identification
   2. Fake News Detection
   3. Political Polarization
7. Introduction to Large Language Models