DCU Home | Our Courses | Loop | Registry | Library | Search DCU

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Natural Language Technologies
Module Code CA4023
School School of Computing
Module Co-ordinatorSemester 1: Jennifer Foster
Semester 2: Jennifer Foster
Autumn: Jennifer Foster
Module TeachersJennifer Foster
NFQ level 8 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
Repeat examination

This module provides students with a practical and theoretical grounding in the following core topics in modern Natural Language Processing: language modelling, language analysis, information extraction and language understanding. Students will learn how these problems are tackled using supervised and semi-supervised machine learning, and they will gain hands-on experience developing machine-learning solutions during the laboratory sessions. Popular benchmark datasets will be employed, including ‘noisy’ datasets containing text from sources such as Twitter and reddit.

Learning Outcomes

1. Describe the applications of Natural Language Processing (NLP) in Data Science
2. Illustrate how neural word embeddings underpin modern NLP systems
3. Develop an English language model
4. Evaluate an English language model
5. Develop an English part-of-speech tagger
6. Evaluate an English part-of-speech tagger
7. Develop a sentiment analysis system for English
8. Evaluate a sentiment analysis system for English
9. Develop an English question answer/reading comprehension system
10. Evaluate an English question answer/reading comprehension system
11. Explain the unsolved problems in NLP research
12. Summarize the ethical issues surrounding modern data-driven NLP

Workload Full-time hours per semester
Type Hours Description
Lecture24Formal lectures introducing NLP for data science
Laboratory12Series of laboratories introducing python-based machine learning techniques for NLP
Assignment Completion21.5No Description
Independent Study130No Description
Total Workload: 187.5

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Language Modelling
Next word prediction using n-gram language models, modern word embeddings including word2vec (Mikolov et al. 2013) and contextualised word embeddings such as BERT (Devlin et al. 2019). Generating text using language models

Language analysis and data extraction
Part-of-speech tagging, dependency parsing, named-entity recognition, semantic parsing. Sequence labelling and structured prediction using recurrent neural nets (LSTMs) and transformer networks

Language understanding
Sentiment analysis, automatic reading comprehension and question answering. Using information retrieval techniques in question answering. Using language analysis and extraction tools (see above) to improve baseline models for language understanding applications

Assessment Breakdown
Continuous Assessment40% Examination Weight60%
Course Work Breakdown
TypeDescription% of totalAssessment Date
AssignmentLanguage modelling10%Week 21
AssignmentPart-of-speech tagging10%Week 24
AssignmentSentiment analysis10%Week 27
AssignmentQuestion Answering/Machine Reading Comprehension10%Week 30
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
This module is category 1
Indicative Reading List

  • Jurafsky and Martin: 0, Speech and Language Processing, Prentice Hall,
  • Manning and Schutze: 1999, Foundations of Statistical Natural Language Processing, MIT Press,
  • Goldberg: 0, Neural Network Methods for Natural Language Processing, Morgan and Claypool,
Other Resources

Programme or List of Programmes
DSBSc in Data Science
MCMM.Sc. in Computing

My DCU | Loop | Disclaimer | Privacy Statement