You’ll probably have some questions about the AI course. Here is a list of our most frequently asked questions. If yours isn’t answered here, feel free to call us or send an email.
Time and Duration
The course starts each year in May, September and January.
The online course takes two years and three months to complete, or you can take up to a maximum of five years to complete it.
A commitment of around 12–15 hours of study per week is anticipated for most students. If you have less experience in particular areas such as maths or programming skills, or have taken a long break from study, you may need to allow more time during some weeks.
Tailored to fit your lifestyle, our online course is perfectly suited to individuals with full-time work and/or family commitments. Online study offers multiple ways to interact with the curriculum, all designed to fit around your schedule.
Tuition fees are paid at £722* per 10 credits. Fees are paid in unit instalments corresponding with the course units. Each taught 10 credit unit is £722 and for the 60 credit dissertation students will pay two instalments of £2,166. To qualify for an MSc you will need a total of 180 credits. All courses will have the dissertation payment split into two equal instalments with the first instalment payable in advance of the start of the dissertation, and the second instalment due during the following enrolment and payment window period (8 weeks after the start of the dissertation).
Although we accept students with a first or high second-class undergraduate degree in any subject, some coding experience is recommended. You will also need to demonstrate evidence of relevant quantitative skills, especially in algebra and calculus.
To enrol on our MSc course, the following criteria apply:
- Typically, you should have a first or strong second-class bachelor’s honours degree or international equivalent.
- You may have an undergraduate degree in any subject, but you must demonstrate evidence of relevant quantitative skills (especially algebra and calculus) either through your degree study or by alternative means.
- If your first language is not English you will need IELTS with a grade of at least 6.5 overall and no less than 6.0 in any of the four parts (listening, reading, writing and speaking). If you completed your degree in the UK within the last 2 years prior to the start of the course, you may be exempt from our English language requirements.
You must demonstrate quantitative skills (calculus, algebra and statistics) through your undergraduate degree, displaying skills beyond A level maths. Quantitative skills developed through work experience can be highlighted in the personal statement.
You do not need a background in programming to study Artificial Intelligence, but you will need to be proficient in maths in order to gain programming skills in the first unit. This course will be challenging if you do not have any programming experience, so we suggest you do some preliminary exploration and practice to gain at least some exposure to programming before the course begins.
Drawing on insights from our Centre for Doctoral Training and our connections with the Institute of Coding, the University of Bath provides a unique perspective on the future of AI in practice. By exploring topics as diverse as data science, robotics, ethics and machine learning, the course provides all the experience you need for a career in this ever-evolving, ever-challenging domain.
Our online environment features regular interaction with your lecturers and fellow students to give it that classroom feel. To help you connect with the content, the environment includes video content, case studies and a library of digital resources. Although our online courses allow you to study at a time and place that suits you, we do ask that you complete your assignments against a set schedule.
The course is 100% online, so there is no need to visit campus at any point during your studies. You can attend campus if you wish, for instance if you want to use the library, but it’s not a requirement.
You are welcome to visit the university if you wish, where you can access facilities such as our physical library, as well as our online library. You can apply for a library card by emailing our library services with your name, address and photo.
Units are run consecutively, with each one taking eight weeks to complete. Over the course of the year, you’ll have three short breaks, in December, April and August.
See how each unit of your course breaks down learning material into bite-size chunks.
Let's look at an example week. So each week that you are doing so each course that you do each unit that you do will be eight weeks. So you will have eight of these pages for each unit at the top you've got an introductory video of taking the sound off you got an introductory video to that week where we talk you through what kind of things you might see in that particular week. And then what we've done here is we've broken down each page into sort of bite-sized chunks. So rather than just giving lots and lots of information we've broken everything into lessons. You'll see the different styles of lessons. So if you see a lesson like this it might have a little bit less information. Whereas one like this basically means an accordion so there's a little bit more information than those lessons.
- Autumn term: September to December
Short break in December
- Spring term: January to April
Short break in April
- Summer term: May to August
Short break in August
The course offers two study specialisms, one exploring the more technical aspects of AI, the latter focusing on the broader, societal dimensions of the subject; both opening up a choice of careers in AI.
Students are assessed through a variety of methods, which could include practical implementations (for example coding), problem sets, reports, group work, case studies, quizzes, and presentations.
We will mainly be using Python. The first unit focuses on getting each student up to the same level of programming in Python.
What we then do once we've presented some content – and this is very specific to principles of programming. The types of exercise that we've got will vary depending on the content, so it sort of lends itself to the type of content that we're teaching in that specific course. For programming the exercises are usually actual practice so practicing coding we can show you lots and lots of text, static text, dynamic text. When it comes to coding the fact of the matter is the best way to learn programming is just to do. It's to make mistakes try again until you're finally getting it. So, this is the best way of basically of learning how to code which is why we've structured it this way.
You will be required to complete a final project to complete your AI online MSc. You can have a look at our AI project page in order to get an idea of which projects AI research groups typically carry out. Both the projects listed on this page, and the projects that our current PhD students do are a good indication of the types of project you could choose to do for your dissertation.
All your required reading will be made available via the University Library’s reading list system and will be available to read electronically. Once you have fully registered as a student and received your university username and password, you will be able to access the Library's services and online resources.
It is recommended you have the following operating systems in order to fully enjoy the benefits of our Virtual Learning Environment (VLE): either Windows 8, 10, or 11, Mac OS X 10.8 or later, Linux based operating systems will likely be sufficient but please note they are not officially supported by our technical support teams. You will need RAM of 4 GB or more and high-speed/broadband connection (at least 25Mbps). If you are unsure, you can test your internet speed here.
It is also important you have an up-to-date web browser, listed here: Chrome (version 30.0 or higher), Firefox (version 25.0 or higher), Microsoft Edge, or Safari (version 6 or higher). Cookies must be enabled in your browser for our VLE to function correctly. Most browsers have cookies enabled by default. If you are unsure whether your browser is configured properly, please contact technical support for advice.
Within the VLE you can access a discussion forum within each unit where you can post questions to your tutor and fellow students. You can also email any questions you may have to your lecturer. If you are seeking support, you can contact our student support team, or if you are having a technical issue, you can ask our 24/7 technical support team.
One of the main forms of interaction is on discussion forums on our VLE, where some of the weekly activities involve you sharing your thoughts in discussions with your fellow classmates. You also have the option to message each other and connect via email, text, WhatsApp and other social media platforms.
This degree has three tenets: theory, practice, and ethics. The University of Bath Computer Science department is theory-led in general; we aim to teach you the skills so that you can easily pick up any specific tools. For example, the first unit currently uses Python.
In some units you will learn the theory of machine learning, so that you understand how the techniques that underpin tools like PyTorch and TensorFlow actually work. Practice is also important, and other units will demonstrate techniques using high-level tools such as these. We try to keep the tools we use in the degree as up-to-date, relevant and useful as possible.
A good programmer can pick up any language. Even if the degree does not cover a specific tool you'd like to use, you will be equipped with the underlying knowledge and experience that will facilitate the process of learning it yourself.
We focus on giving people the knowledge and experience of solving AI problems by both implementing algorithms themselves as well as using existing libraries. Example of libraries include NumPy, Pytorch and Tensorflow. The emphasis is on understanding AI theory and practice so you can not only ‘solve’ a problem with specific libraries or techniques today, but also ensure you have the skills to adapt to new approaches and libraries in the future.
All courses at Bath take a theory and practice approach to teaching. We introduce a concept and ask you to apply it in a given context. AI is a constantly evolving field of research and development, so the theory behind it is crucial. Also important are the ‘soft’ skills we teach you, for example, being able to research new libraries and techniques and apply them to a problem.
You will not need to download new software in this course to learn programming. Discover how the University uses an online platform called Repl.it to practice coding.
Now a question I often get is: “what do I need to download what am I going to code in for principles of programming?” You won't need to download anything. So, we program in an online coding environment called Repl.it. We call it basically what this is. It's sort of a place that we can embed into these pages where you can then go in and change the text, so you'll be able to change the text you'll be able to run the code. You'll be able to see what it does here now if you wanted to actually do the assignment which is to edit the code to print something different, you're welcome to do it here what you can also do is open it in Repl.it. So, what that does is it opens up a new page and it shows the code here. Now the thing that I hear a lot of questions about is: “well if I change this won't I change so the master code?” You won't. So, what if the magic of having logged in before is I’ve already created an account. I’ve already logged in. This is something that we'll be asking you to do pretty much at the start of week one. But what I would do here is if I make any changes. What it does is it switches to my account and then I can make changes to the original here like that.
You will write and submit code for credit using lab sheets. As you complete your lab sheets, you can use the unit’s discussion board to get help from your peers and instructor.
So that was an example lesson: a few pages of content and then an exercise. Let's go to the end of the week then. So, towards the end of the week, we've then got lab sheets in this particular unit. So in the lab sheets what we usually do is we get you to actually write code here. Now the lab sheet won't be a single question – it will usually be multiple questions. Same thing again you edit the code you create your own answers to these questions and then you post them on the lab sheet. What we've then got is a discussion forum and in the discussion forum we ask you to sort of start discussions with each other, but also ask questions for us. So, if it's lab sheet specific post some questions in here say: “I couldn't figure out how to do this particular thing does anyone have any ideas? Does anyone have any suggestions?” Specifically, you know we ask quite openly here: “how are you doing with the lab sheets?”, “Are you finding anything difficult?”, “If you did find something difficult and you fixed it: what kind of tips would you have for your classmates?” So this is the sort of thing that we're looking for here.
Learn how you will navigate the virtual learning environment. This video walks you through how to get to the unit overview, learning outcomes, and available resources, as well as your assignments and grades.
All right let's get back to the main page. So the first thing is that you'll see in each unit is this welcome page. (Let's see if I can mute the…it's muted great stuff!) So in the welcome page you will have a video which is an introduction to the course itself. Under here you'll have lots of resources that you can go to. We'll have a unit overview – so that will be information about what we're trying to teach in this particular unit. And then we also have your learning outcomes.
So let's say these specific ones are sort of the ones that you would go and have a look at as you start each unit. The following resources I would say you probably end up coming back to multiple times throughout your studies. And those are for example greater tests and assignments. This is a really great one it gives you an overview of exactly when your graded tests are due. Obviously these are dummy dates. But exactly when your graded tests would do anything that you need to do in order to succeed in this particular unit. So you've got your due dates in here. We want to make sure that we present this to you for every course for every unit that you take, because it's with the understanding of course that this is this is a part-time degree and therefore you everyone is busy. We're all busy people and so this is a chance to sort of have a look in advance and see when is it when am I going to be working a little bit harder perhaps because I’m working towards a graded assignment.
Thanks to the relevance of artificial intelligence in multiple industry sectors, and the broad range of subjects covered, this course unlocks career opportunities across the board. Whether you are looking to expand into a more technical or strategic role, this course will support you.
The degree certificate and transcript do not mention ‘online’, and the degree qualification is equivalent to a full-time campus degree.