About the course
Data is one of today’s most valuable commodities and AI touches almost every walk of life. From improving diagnosis and treatment in healthcare to offering new creative tools for artists.
Our MSc offers a fast-track to career success in this field. You’ll develop key skills including programming, problem-solving, and data visualisation and interpretation.
At the end of the course, you’ll be able to apply these techniques to real-world problems. You’ll have the knowledge to test methodologies. As well as the skills to plan, design and carry out empirical research.
How you’ll learn
- Intensive on-campus teaching, normally one day a week
- Based at our state of the art DAIM building
- Lectures, workshops and a self-led research project
- In-person sessions focus on problem-solving and group work
- Spend the remaining time outside of lectures and teaching, to complete your coursework and implement the skills you have learned
What is ‘intensive teaching’?
It’s normally one full day of in-person teaching from 9 am to 6 pm. All your in-person lectures and workshops will usually be on this day.
So you generally only need to commute to campus once a week. Perfect if you’re travelling far to get here, or need to be flexible for work or childcare.
Who this course is for
Want to change direction? Switch careers? Or upskill? Our MSc is for you. It’s a fast-track Masters-level conversion course. Which means anyone from any academic background can apply to study it.
Our students join us from a range of STEM and non-STEM subjects. English Literature, Maths, Music, Politics, Psychology, Physics, Marketing, Biology, Computer Science, and more.
Don’t have programming experience? That’s okay. You’ll learn Python coding at the start of the course to make sure you’re up to speed.
So if you’ve completed a related undergraduate degree, that’s great. But if not, we’d still love to hear from you. You bring your ideas, energy and experience, we’ll teach you the rest.
This course is closed to International students for study in September 2023.
If you are a home (UK) student and want to study this programme in September 2024 please contact admissions on 01482 466850 or firstname.lastname@example.org.
The January 2024 intake is available for full-time study only and is open to both UK and international applicants.
Artificial Intelligence and Data Science Bursaries
To support widening participation students studying this course in January 2024/25, a round of scholarships worth £10,000 are available to applicants, which will be prioritised for women, black, disabled or low-income background students.
Find out more and apply now.
What you'll study
Unlike other universities, you’ll cover the full breadth of AI – not just one specialism. From programming and machine learning, to big data and ethical responsibilities.
Take one AI and one data science module, together with the programming module.
Advance your AI and data science skills with further modules. And prepare for your dissertation by exploring case studies and working on a research proposal.
Trimester 3 (Dissertation)
An opportunity to choose your own research project in a disciplinary area relevant to your background or career goals. Alternatively, there may also be an opportunity to undertake a project working with one of our industry partners, solving real-world problems.
Our partners include Humber Outreach Partnership, Naimuri, Spencer Group, J.R Rix & Sons, KCOM, The Deep, Lampada Digital Solutions, Optalysys and C4DI.
All modules are subject to availability and this list may change at any time.
Programming for AI and Data Science
The module content is designed to ensure that you are equipped with the fundamental programming skills in Python to allow you to successfully undertake the remainder of the programme.
Techniques that will be taught include:
• Installation and Packages, including specific packages for machine learning, data science, and artificial intelligence.
• Fundamentals of coding
• Documentation, File Handling and Lists, Variables and Data Types, Functions and Loops, Conditions and Data Manipulation, Graphing and basic visualization, Debugging and testing.
This module is assessed by a portfolio of work.
Fundamentals of Data Science
An introduction to the principles of data science and data analysis. Topics include:
• Data Science Context: Datafication of society and the history of data science; Properties and types of data (e.g., quantitative and categorical data)
• Classification and regression, introduction to Kaggle and other sources of data
• Data Management: Data collection and techniques; Cleaning of data and processing; Data errors and artefacts; missing data
• Introductory statistical approaches to data: Introduction to probabilities; Descriptive statistics (e.g., centrality measures) and characterizing distributions; Correlations; Statistical hypothesis testing
• Data analysis and visualization: Types of visualization and interpretation; Regression models
• Applications: Real-world data applications, including examples
• The legal framework and ethical implications of data science
This module is assessed by a presentation and project report.
An introduction to the fundamental concepts in Artificial Intelligence, and their application. Topics include:
• Origins of AI: What is AI?; From early history to the Dartmouth conference and the present day; Intelligent agents, and performance measures.
• Learning, Frameworks and Packages: Introduction to supervised and unsupervised learning; Convolution neural networks, Capsule neural networks; Keras; Tensorflow
• Implications for Society: Legalities; Ethics and professional implications; Social consequences
This module is assessed by a portfolio of work.
Big Data and Data Mining
This module gives students a range of practical applications of data science by examining closely how we mine data from big data sets. This covers a range of approaches from pattern association to network analysis and is underpinned by an ethical framework.
Applied Artificial Intelligence
The module will build on the concepts introduced in the first Artificial Intelligence module and provide you with the skills and knowledge to undertake your dissertation. Topics will include:
• Classification: revisiting the classification problem; Hyperplanes; Naive Bayes classifiers
• Deep Learning: neural networks; Autoencoders and Deep Learning
• Applications to problems: real-world problems, and solving them with AI, Natural language processing
• Legal, societal, ethical and professional implications of using AI, including cognitive bias in AI solutions and the implications for equality.
This module is assessed by a presentation and a project report.
Research and Application in Artificial Intelligence and Data Science
This module offers options in how Artificial Intelligence and Data Science are applied to
real-world contexts. By the end of the module, you will have formulated your own plans and literature reviews for your final MSc project. The module contains two themes that are strongly inter-related to each other.
Theme 1 – Options
You will be offered a selection of tailored studies in Artificial Intelligence. These options will comprise:
Option 1 – Sustainability
Option 2 – AI in Healthcare
Option 3 – Social Responsibility
Option 4 – The Creative Industries
Option 5 – The Natural Environment
Each of these options represents a specialist application of Artificial Intelligence and Data Science into a particular area. This will enable you to select and investigate applied aspects of AI and Data Science taught by specialists in this area and to consider projects in these areas, which is related to Theme 2.
Please note that not all of these options will necessarily run in every year and will be dependent on demand.
Theme 2: Research Proposal Development
In tandem with the first theme, you will develop with guidance your own research proposal to tackle a genuine research project. This will prepare you for the MSc research project and dissertation in the final trimester. You will draw from the experiences in the options to identify questions and limitations associated with your proposed research.
Artificial Intelligence and Data Science Research Project
This module is the capstone of the MSc, drawing together the skills and knowledge built up through the programme and allowing you to demonstrate your competence in using AI and/or data science techniques.
This module aims to develop your ability to:
• Plan and work independently on a complex research-based problem in artificial intelligence and/or data science.
• Report on the aims, methods and outcomes of a scientific investigation.
Each research project will be particular to the individual concerned. The actual work carried out will depend on the topic but may include experimental planning and organisation of equipment and/or services (e.g., VIPER), computer programming in artificial intelligence and/or data science, data acquisition and analysis, study of related literature and critical evaluation of the outputs.