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MAI4CAREU - Natural Language Processing - Distributed Contextual Embeddings

MAI4CAREU - Natural Language Processing - Distributed Contextual Embeddings

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 fifth lecture of the course provides an introduction into ‘Distributed Contextual Embeddings’. The lecture then looks at: 

  • The history of Neural Language Models such as:
    • Recurrent Neural Networks (RNNs)
    • ELMo
    • GPT
    • BERT
  • The inner-workings of Transformers and fine-tuning approaches, including Masked Language Modeling and Next Sentence Prediction

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
     

Learning content

Target audience
Digital skills in education.
Digital skill level
Geographic scope - Country
Austria
Belgium
Bulgaria
Cyprus