Description
This module will introduce the basic concepts, theories and terminology of Artificial Intelligence (AI) and Machine Learning (ML). You will gain knowledge of a variety of AI methods including classical approaches, through to contemporary methods such deep neural networks as well as modern AI trends. You will be able to apply AI to problems, which may involve labelling, building, training, and deploying a machine learning model.
Aims
This module aims to provide an accessible introduction to AI/ML concepts and theories and practical experience of applying ML/AI to real world problems.
Learning Outcomes
By the end of this module the student should be able to:
- Describe basic concepts and theories in Artificial Intelligence and appreciate their advantages and disadvantages in various application domains.
- To examine and apply ML/AI techniques to solve real-world problems.
Indicative Content
1 Classic, Current & Modern AI/ML methods
Introduce the basic concepts, theories and terminology of Artificial Intelligence (AI) and Machine Learning (ML) as per the three waves of AI - classic, current and modern approaches.
2 Introduction to Machine Learning
What is ML? ML process, business problem solved with ML, ML tools, ML challenges, supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), reinforcement learning, etc
3 Understand the ML pipeline
Formulating ML problems, collecting and securing data, extracting, transferring and loading data, evaluating your data, finding corelation, feature engineering, data cleaning, dealing with outliers, training, deployment, performance evaluation, hyperparameters and model tuning
4 Computer Vision
Facial Recognition, Image and Video Analysis, Dataset Preparation
5 Natural Language Processing
Introduction and use in translation and chat bot services
| Teaching and Learning Method | Hours |
|---|---|
| Lecture | 0 |
| Tutorial/Seminar | 0 |
| Supervised Practical Activity | 0 |
| Unsupervised Practical Activity | 0 |
| Assessment | 30 |
| Independent | 120 |
Guidance Notes
SCQF Level - The Scottish Credit and Qualifications Framework provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.
Credit Value – The total value of SCQF credits for the module. 20 credits are the equivalent of 10 ECTS credits. A full-time student should normally register for 60 SCQF credits per semester.
Disclaimer
We make every effort to ensure that the information on our website is accurate but it is possible that some changes may occur prior to the academic year of entry. The modules listed in this catalogue are offered subject to availability during academic year 2025/6, and may be subject to change for future years.