Last modified: 12 Sep 2024 14:46
Natural Language Processing (NLP) is an influential interdisciplinary topic that relates to the disciplines of Artificial Intelligence, Linguistics, Psychology and Human Computer Interaction, amongst others.
NLP engineers are in high demand both in big tech companies, as well as smaller companies, as contemporary tools encourage businesses to make better use of their textual data or inspire, design and create new language technologies.
This course covers a range of theoretical and applied topics related to computational linguistics: how to analyse text data, how to model it, how to generate it and how to evaluate NLP projects. Key topics include text analytics, text classification, language modelling, syntax, semantics, pragmatics and evaluation.
| Study Type | Undergraduate | Level | 4 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This course introduces fundamental techniques for a range of tasks in Natural Language Processing (NLP). This course aims to explain the potential (and main limitations) of these techniques, as well as to discuss them in the wider context of contemporary NLP research, and their real-world impact.
The course will cover the following indicative range of topics interspersing linguistic theory with fundamental approaches and selected applications:
Lexical Processing
• Text pre-processing techniques
• Simple text classification
• Part of speech tagging
• Language modelling
Syntax and Structure
• Syntactic hierarchy
• Grammers
• Parsing
• Annotations
Semantics and Pragmatics
• Meaning and concepts - word and sentence representations
• Discourse structure
• Reference
• Modelling dialogue phenomena
• Speech acts
Multilinguality
• Machine Translation
• Multilingual Language Models
Applications
• Search
• Summarisation
• Generation
Evaluation
• Bias in data
• Interpretability
• Human Evaluation
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 20 | |
|---|---|---|---|---|
| Assessment Weeks | 17 | Feedback Weeks | 19 | |
| Feedback |
Feedback via MyAberdeen |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Analyse | Students will be able to think analytically and creatively about how to solve applied NLP problems |
| Conceptual | Understand | Students will demonstrate mastery of core principles and concepts of Natural Language Processing practice and theory |
| Procedural | Apply | Students will demonstrate the ability to apply relevant NLP techniques to practical and theoretical problems. |
| Procedural | Evaluate | Students will be able to analyse and evaluate the success of NLP systems, designing and conducting appropriate evaluations. |
| Assessment Type | Summative | Weighting | 70 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Generic feedback via MyAberdeen. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Analyse | Students will be able to think analytically and creatively about how to solve applied NLP problems |
| Conceptual | Understand | Students will demonstrate mastery of core principles and concepts of Natural Language Processing practice and theory |
| Procedural | Apply | Students will demonstrate the ability to apply relevant NLP techniques to practical and theoretical problems. |
| Procedural | Evaluate | Students will be able to analyse and evaluate the success of NLP systems, designing and conducting appropriate evaluations. |
| Reflection | Create | Students will be able solve NLP problems to communicate results effectively and at an appropriate level of technical depth. |
| Assessment Type | Summative | Weighting | 10 | |
|---|---|---|---|---|
| Assessment Weeks | 14 | Feedback Weeks | 14 | |
| Feedback |
Feedback via MyAberdeen Duration: 1 hour within 24 hours |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Understand | Students will demonstrate mastery of core principles and concepts of Natural Language Processing practice and theory |
| Procedural | Apply | Students will demonstrate the ability to apply relevant NLP techniques to practical and theoretical problems. |
| Procedural | Evaluate | Students will be able to analyse and evaluate the success of NLP systems, designing and conducting appropriate evaluations. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Reflection | Create | Students will be able solve NLP problems to communicate results effectively and at an appropriate level of technical depth. |
| Conceptual | Understand | Students will demonstrate mastery of core principles and concepts of Natural Language Processing practice and theory |
| Procedural | Evaluate | Students will be able to analyse and evaluate the success of NLP systems, designing and conducting appropriate evaluations. |
| Procedural | Apply | Students will demonstrate the ability to apply relevant NLP techniques to practical and theoretical problems. |
| Conceptual | Analyse | Students will be able to think analytically and creatively about how to solve applied NLP problems |
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