The University of Sheffield
School of Computer Science

COM4513 Natural Language Processing

Summary This module provides an introduction to the field of computer processing of written natural language, known as Natural Language Processing (NLP). We will cover core concepts, models and algorithms for analysing and processing natural language data, exploring a range of approaches used in contemporary NLP systems, and discussing their strengths, limitations, and applications.
Session Spring 2026/27
Credits 15
Assessment
  • Assignment [30%]
  • Formal examination [70%]
Lecturer(s) Dr Nafise Sadat Moosavi & Prof. Nikolaos Aletras
Resources
Aims
  •  to give students a well-rounded understanding of Natural Language Processing (NLP), including its key concepts and approaches.
  •  to give students an understanding of the potential areas of application of NLP techniques.
Learning Outcomes  By the end of this module the student should be able to:
  • Describe and discuss the main subareas, concepts and approaches in Natural Language Processing. 
  • Apply NLP algorithms and techniques.
  • Describe and discuss the potential and limitations of NLP techniques in real-world applications.
Content

 The module provides a comprehensive introduction to Natural Language Processing, combining essential fundamentals with coverage of contemporary neural and large language model approaches. The first part of the course offers a focused recap of core NLP concepts; the second part covers modern deep learning, Transformers, and large-scale language modelling. Throughout, students will engage with both the theoretical foundations and practical implementation of NLP systems.
Restrictions

This module is only open to students who have taken Text Processing (COM3110/COM4115/COM6115) and Machine Learning and Adaptive Intelligence (COM4509/6509).

Optional modules within the school have limited capacity. We will always try to accommodate all students but cannot guarantee a place. 
Teaching Method There will be 2 formal lectures and 1 lab session per week.
Feedback Written feedback for the assignment
Verbal interaction during lectures and lab sessions.