The power of artificial intelligence (AI) and data science is rapidly changing our world. Be part of the next industrial revolution.
Data is one of today’s most valuable commodities. AI touches almost every walk of life – from improving diagnosis and treatment in healthcare to new creative tools for artists.
The need for skilled graduates who understand the full breadth of the technology is greater now than ever before.
About this course
Want to change direction? Switch careers? Upskill? This fast-track Masters is for you.
Taught in our £4.5 million Centre of Excellence for Data Science, Artificial Intelligence and Modelling (DAIM), our MSc offers a fast track to career success in this dynamic field.
As a conversion course, this MSc is suitable for students with a range of backgrounds in STEM and non-STEM subjects. With intensive teaching, your in-person lectures and workshops will normally be one day a week, 9 am to 6 pm, so you can balance your studies alongside other commitments.
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.
Unlike other universities, you’ll study the full breadth of AI, not just one specialism. You’ll cover programming, statistics, machine learning, big data, data visualisation, computer vision and the ethical and legal responsibilities of using data.
You can design your own research project to suit your background and career interests. Some students may be able to with work on a research project with one of our industry partners such as Naimuri, the NHS, KCOM or Lampada Digital Solutions.
You’ll develop key skills including programming, problem-solving, and data visualisation and interpretation. And graduate at the forefront of data science.
Module options
For a full Masters degree, you'll study 180 credits over the duration of your course. Some programmes offer a Postgraduate Diploma (PGDip) qualification or a Postgraduate Certificate (PGCert) qualification. For a PGDip, you'll study 120 credits, and for a PGCert, you'll study 60 credits.
Filters
Programming for AI and Data Science
Learn the fundamentals of Python coding so you can progress onto the rest of the course.
Assessment: Portfolio of work
core
20 credits
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: Basic mathematical concepts; 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; Identifying outliers; Regression models
- Applications: Real-world data applications, including examples
This module is assessed by a presentation and project report.
core
20 credits
Understanding Artificial Intelligence
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 learning; Regression; Classification; Clustering; Artificial Neural Networks; Convolutional Neural Networks; Keras; Tensorflow
- Implications for Society: Legalities; Ethics and professional implications; Social consequences
This module is assessed by a portfolio of work, in the form of a programmed code and a corresponding technical report.
core
20 credits
Big Data and Data Mining
The module will build on the concepts introduced in the first data science module and introduce Big Data and Data Mining, including network analysis. Topics will include:
- Databases, including the use of the SQL language.
- Association Pattern Data Mining: the Brute force approaches and A priori algorithm.
- Sorting Algorithms: Bubble sort
- Clustering: DBSCAN
- Time series analysis: ARIMA: XGBOOST
- Web Scraping/spidering: Beautiful Soup; Legal and ethical aspects
- Network Analysis: social media, graph theory, network visualisation and similarity measures
This module is assessed by a presentation and a project report.
core
20 credits
Applied Artificial Intelligence
The module will build on the concepts introduced in the first AI module, and prepare you for your dissertation. Topics include classification revisited, deep learning, applications to problems, cognitive bias, and implications for equality.
Assessment: Presentation and project report
core
20 credits
Research and Application in Artificial Intelligence and Data Science
The module contains two themes that are strongly interrelated to each other:
The first theme offers options to study how AI and Data Science apply to real-world contexts. Options could include sustainability, healthcare, social responsibility, the creative industries, and the natural environment.
Alongside the first theme, you’ll develop your own research proposal to tackle a genuine research project. You’ll draw from the experiences in the options to identify questions and limitations associated with your proposed research. This will prepare you for your dissertation in Trimester 3.
core
20 credits
Artificial Intelligence and Data Science Research Project
Plan and work independently on your own complex research-based problem. And report on the aims, methods and outcomes of your scientific investigation.
core
60 credits
Our academics
You’ll be taught in DAIM – a centre of excellence created for this course, drawing on expertise from across the whole University.
Our academics’ broad specialisms include computer science, machine learning, AI, astrophysics, mathematics earth sciences, geospatial, music, engineering, ethics and medicine.
Kevin Pimbblet
Director of DAIM; Professor
Kevin is an experienced British-Australian observational astronomer and applied data scientist, having worked in multiple research intensive institutions across two continents. His core research interests cover a number of astrophysical topics.
Will Jones
Lecturer & Director of Research
Will is Director of Research for the Centre of Excellence for Data Science, AI, and Modelling. Will also holds an Honorary Contract with Hull University Teaching Hospitals (HUTH), NHS, as a Researcher in Medical Oncology.
Entry Requirements
What do I need?
When it comes to applying for this Postgraduate Taught degree, you'll need an Undergraduate degree (or equivalent). For this course, you'll need a 2:2 from a relevant bachelor's degree.
The programme is designed for graduates who have a studied a subject that is relevant to this course.
If you’re an undergraduate student at Hull, you’re guaranteed a fast-track route to this postgraduate degree, as long as you meet the entry requirements.
In order to ensure our students have a rich learning and student experience, most of our programmes have a mix of domestic and international students. We reserve the right to close applications early to either group if application volumes suggest that this blend cannot be achieved.
Typical offer
2:2 in a relevant subject area
Your degree should have strong numerical content.
Fees & Funding
How much is it?
Scholarships
We offer a number of awards, bursaries and scholarships for eligible students. They’re awarded for a variety of reasons including academic achievement and/or to help those on lower incomes.
Scholarships and bursaries are separate to student loans. And the best bit is, you don’t pay a penny back.
Alumni Postgraduate Scholarship
University of Hull undergraduates progressing to a taught masters course may receive a 20% discount on the cost of their tuition fees.
Find out if you’re eligible by visiting the University of Hull Alumni Postgraduate Scholarship page.
See more Scholarships
We offer a range of scholarships and awards to students at the university to help with their financial load.
To view all of our scholarships and determine whether you're eligible, please visit our Scholarships and Awards page.
Artificial Intelligence Facilities
Future prospects
There’s a shortage of qualified data practitioners to meet the growing needs of employers. So you’ll be in high demand.
You’ll graduate the ability to apply AI and data science techniques to real-world problems. And could go on to work as a data scientist in a wide range of industries. Our recent graduates have joined big names such as Amazon and Scottish Power.
You’ll also be able to critically evaluate AI and data science methodologies. Plan, design and carry out empirical research. And interpret, present and communicate the outcomes of data science and AI solutions. Which means you’ll be ready to progress to further study in a broad variety of subjects.
Take your career to the next level
Like what you’ve seen? Then it’s time to apply.
Make your application online now, and our admissions team will get back to you as soon as possible to make you an offer.
Not ready to apply yet?
We regularly deliver virtual and on-campus events to help you discover your perfect postgraduate course, whether it’s a subject you already love or something completely different. Our events are an opportunity for you to chat to tutors and current students and find out about the career options a postgraduate degree could lead to.