PG on-demand content session 1 - AI and Data Science MSc

Hello everyone and welcome to our Postgraduate on-demand content series. My name is Lauren. I'm the Postgraduate Marketing Manager here at Keele University. Pleased to introduce this session which is led by Professor Ed Quincey, our programme lead for AI and Data Science, who will share his insights and expertise.

Thanks, Lauren. So yeah, so I'm here to talk today about our MSc AI and Data Science course in the School of Computer Science and Mathematics at Keele University. I thought it'd be useful just to briefly give you an overview, a bit of context about our school, the school that I work in. Because we do offer more than Masters programmes. We offer our undergraduate programmes: BSc programmes in Computer Science, Data Science and Maths.

We also offer eight specialist pathways in areas such as AI, Cybersecurity, Pure Maths, Applied Maths, Statistics. And our MSc programmes, as well as our AI in Data Science course, we also offer MSc programmes in Computer Science, Cybersecurity, and we also offer some 100% online MSc degrees as well.

So the course that you're interested in is our MSc AI and Data Science course for September 2025. We've totally redesigned this course. So it launched in about 2020, and we sort of iterated over the past 4 or 5 years. We felt it was time to totally refresh it. And so we have all new modules. We have a number of larger modules called 30 credit modules, and these allow for increased content scope and focus in our delivery. And we also have a January start for this programme as well.

The main aim I had when we redesigned the course was to focus on employability, because our assumption from chatting to students, is that if you're going to come and do a masters course with us, you want to get a good job in the end in related industries.

So the course, is balanced between technical skills, which I'll talk to you about in a second. But also we cover professional issues and relevant standards as well. Things that employers want you to know about as well as having technical skills. The thing to note is that the course is suitable
for students from all disciplines. And when we say that, we do really mean it. They’re called conversion courses, which are for students from any background.

So when it comes to employability, you will have access to four different types of industrial experience. So in the taught component of the course, we have industry guest lectures and seminars that are routinely delivered as part of the course and within the school as well. We have industry related projects as part of our Advanced Research and Development project module over the summer. And I'll show you some examples of that in a bit.

We also have, over the summer, an Industrial Placement Project module. So this is where you do an 8 to 12 week placement with a relevant company. And you choose between the Advanced Research Development Project and this Industrial Placement Project.

We also offer the option to extend your degree so that you can get a 'with placement' degree. This is where you do a 6 to 12 month placement, as part of a two year course. So you do that after you've done the main 180 credits.

And just to show you that I have really thought about this, World Economic Forum, every so often, asked businesses what their top ten skill priorities are. And in 2027, you've got the ten here. And I think the majority of our courses, and particularly the MSc AI and Data Science course, covers all of these skills that employers are looking for. So going beyond technical skills, things like analytical thinking, creative thinking, resilience, flexibility, curiosity, of course technological literacy, motivation, empathy and so on.

Yes, you will learn technical skills and I'll show you what those are in a second, but we're also considering the other things that employers want in more general terms.

So this is what the course, looks like. So this is for our September starters. So in semester one, and both of our semesters, we teach in six week blocks. This gives you an opportunity to focus on particular areas, but it also means that, in semester one when you come to us, we give you the skills that are needed for the rest of the course. These are sort of almost mini bootcamps. You start with a maths module, which gives you the maths knowledge that you need for AI and Data Science. You also do a Foundations of Programming in Software Engineering module, and this is basically where we teach you Python programming.

You then move into in block B and so in the next six weeks before the winter break in the UK, we have an Ethics, Governance and Professionalism module. So it's not all just about technical skills. One of the things that employers are definitely looking for is knowledge of ethics and understanding of ethics when it comes to AI and Data Science. And also the other thing that's in this module is that we will have things like support from career services and our placements team to try and help you find the job and sort of sculpt the job that you want and to reflect on the skills that you need to develop during this course.

After the winter break in January, you'll come back and you'll do a module in Data Management and Cloud Technologies. Then after that, this is sort of where the core skills are then learned. It's when you do the module on advanced applications of AI and machine learning. So again, a six week, 30 credit module, and that's all you'll be studying. All of the content is in there allows you focus on the assessment for that particular topic area as well. Then over the summer and of course semester three, so June to September, this is where you get the choice whether to do an advanced research and development project, or industrial placement project.

So just to show you - this is if you're interested in January start with us. All of the modules are the same, it just sort of happens in a slightly different order. You come in January and you do, maths and programming. You then pick up the advanced applications of AI and machine learning module. You then start the summer with the data management and cloud module. And it's then at this point that you can do, the Advanced Research Development project or the industrial placement project. And once you've completed those, you come back basically and complete the last taught module in ethics, Governance and Professionalism.

Just so if you're worried and you're thinking, well, I haven't done all of the taught modules before I do placement or a project. What we've done is carefully picked the content that goes into the sort of semester two and semester three start modules. So we believe that you will be able to get a placement. And we have had students January starting students that have got placements and then very good projects. And our previous courses had a similar structure.

I think it's important to highlight who you're going to be studying with as well, so sort of the cohort that you'll be with. You will be studying the students, from a mix of all of the two courses as well. So cybersecurity and computer science. In our welcome week, you'll meet students from all of the courses. You'll be doing some group tasks. So you get to know people, and again, in the maths and programming modules there will be a mix of students in those, The program specific modules that I've just shown you, you'll be with your own program cohort. There will be a mix of September and January starting students there. The data management and cloud module, is mixed across all programs. And again, the project industrial placements, although that's basically an individual thing that you'll be studying, we do have a project poster event which will bring all students together as well. So a combination of studying with students from the same discipline, but doing slightly different courses, but there will also be specific modules that only AI and Data Science students are studying.

So some of the skills that you'll develop. I don't intend to go through all of these, because particularly if you're not from a computer science background, they won't mean much to you. But I just want you to be aware that we've really thought about these are the topic areas, these are the skills that we believe,
and companies believe that graduates, need to go into this area. You will, do teamwork, communication, presentation skills and so on. You'll learn how to program in Python, as I mentioned. You'll be doing maths things like doing linear algebra, probability, statistics. And then there's the data management and cloud module. And this is where you'll learn how to store data, how to clean data, big data technologies, cloud platforms you'll be learning about, in particular Amazon Web Services. So that just gives you an idea of some of the skills that all students on our courses learn.

Now, in particular for the AI and Data Science course, you'll be learning about data visualization, machine learning, different types of supervised/unsupervised learning, neural networks and so on. And again, for some of you, these may sound quite scary, but we are pitching this knowing that a lot of you won't actually have, any knowledge of what these things mean. Again, just feel safe that we have picked these knowing that these are the sorts of things that you need to know, and hopefully the sorts of things that you'll find exciting and interesting because they're the sorts of things that we find exciting and interesting as well.

To give you a bit of a background of the course and some more information you may find interesting; I set this up in 2020. We received over 1 million pounds funding from the UK government, and this enable scholarships for 75 students to come and study with us from all over the world. These scholarships were particularly for students from underrepresented groups, so, black, female and disabled students. What's great about that? That's had a real impact on the diversity levels, not only in the field in general as this was across the UK, but also at Keele, Importantly as well, for some of you, 41% were from far non-STEM backgrounds as well, so not from a computing discipline. I hope that gives you an idea of the diversity that we have at Keele. We’re also linked with the Alan Turing Institute, which is the UK's National Institute for Data Science and AI. Just so you’re aware we have co-designed this in collaboration with local and national employers. So we know that it meets the needs of students from various academic backgrounds as well.

So the support and teaching that we have with Keele. Keele University is one of the first universities in the UK to actually teach computing over 50 years ago. We have a strong tradition, at least over 25 years in supporting students from other disciplines into computing related careers. Just so you are aware, I am one of those students. I did a master's course at Keele, 20 plus years ago now. My first degree was in biology, so I know that this can work and does work. Our modules in 2025, we plan to be teaching those with full time members of academic staff. We have high levels of student support. There's one-to-one support in practicals. We also offer weekly online help desks as well. And of course, myself and my colleagues are available in office hours as well to answer any questions that you may have. I do want to emphasize we have lots of practical based, sessions every week, and that's where you'll do the real learning. That's where I want to put the emphasis - there is lots of support in those practical sessions.

And as I mentioned, we have this six week block structure that is designed to support students from non-computing backgrounds. As I said, it allows you to focus on particular topic areas. One of the places that you'll be studying in is the Central Science Laboratory. The top floor there is a huge suite of PCs that are regularly updated. We also have green high performance computing available at Keele, which isn't necessarily part of the course, but some project students do use that facility. And of course, you'll have electronic access to the books, journals, databases from relevant organizations like ACM and IEEE as well.

These are some links to news articles over the past year that my colleagues and myself, which highlights work that we've been involved in. Again, this gives you a flavour of some of the things that we do. So you can see here we've been developing emotionally aware chat bots. We've been looking at digital connectivity, so things like sort of 5G, 6G and beyond. We've been looking at developing AI tools to detect fake news. I've been looking at online hate speech. We also have been creating collaborations with other universities around the world looking at opportunities for AI in Malaysia, and a partnership with the German Aerospace Centre as well.

The interests that myself and my colleagues have, feed into the projects that we propose as part of the Advanced Research and Development project module. Examples here, we've got a colleague looking at large language models and software engineering. A student worked on that project with that member of staff and that was recently published in a high quality journal, so that student now has a first author journal article publication based on the project that they did over the summer with us. We've had a student look at something called a deep neural network, and look at that for structural component recognition, and again this was written up for a conference this time. The student and my colleague presented this paper at the 18th
International Conference on Computer Vision Theory and Applications. So again, you can see how this potentially could lead into an academic career,
if that's something you're interested in. But even if not, this is something great to have on your CV to have a peer reviewed publication. Not many students end up having that after their master's course. We've had students that have worked with looking at detection of marine life, and this was with a company protecting ecology beyond land, and now that student having done the project, with them, is now working as that company's embedded systems engineer. And then the last one there, this is again with a local company who develops systems for farming. They were looking at something called attention models for clover plant leaf detection, but again, just to show you that not all of these things are academic, they could actually be working with a company as well on a particular project.

The industrial placement project module, these are some recent example placement companies that we've had. So national companies in the UK: Allstate Northern Ireland, a student as a data science intern this year, and she's now got a job at that company. A company called Booker Wholesale 4PS Construction Solutions, dotConnect Solutions, so a wide variety of different types of company that have placed our students in the UK. But also wanted you to know that, we've had students placed at other universities as well. So we've actually done the placement project module at places like Imperial in London, Harper Adams University which is a local university to Keele, and also the University of Bristol there. They're predominantly because we have research connections with those universities, and those universities are looking for someone to do some work and be placed there over the summer and that can then be part of this module. We have students working being placed in the NHS, and the government. And also at Keele, what's great is Keele’s campus is huge and it also hosts a lot of companie,s and a lot of tech companies as well so we've had a number of students placed at companies called Mondrem and Concentric Solutions, and a number of them are now actually working at those companies as well.

How will you be assessed? The idea is that with assessment, it's authentic and applied wherever possible. We give you industry relevant case studies, industry relevant data sets to work with. Sometimes in some modules we’ll give you the choice of data sets and scenarios as well so you can try and focus that on the area that you want to go into. There are some recorded demos and presentations that you'll do as well, which is a useful skill for industry. And there are group work components in at least one of the modules that you'll study, but that's really, really important because that's a skill that all employers will be looking for.

So other opportunities, that are extracurricular to the course, but, that we do have at Keele. We are one of the Google Cloud partner universities and on a program where they offer access to their online learning platform. So there are some online courses that you can do that are then supported by Google as well, with some drop in sessions that they offer online. And we're also part of the Amazon Web Services Academy. We have a sandbox environment that's supplied by Amazon Web Services that is integrated into one of the modules. And also, we have just been accepted on the AWS UK Cyber Education Grant program, which gives for projects over the summer, some credits that you can use and some projects that you can be working on as well. The thing at the bottom there is the flourish program. And this just gives you an idea of other things that Keele offer.

Other things that I think are worth highlighting. We have strong career support at Keele. We have a really good placements and project team who are there to try and help you find these placements. We also have close links with what's called Universities Digital Society Institute, which is a building on campus that we can work in, but also has lots of tech companies as well. Some of the ones that I mentioned before are actually placed in that Digital Society Institute building that we are connected with, and so that means that we have access to companies on campus, for you to do your placements at.

As I mentioned right at the start, one of the key things that we assume is that you want to get a job after this and there's two surveys here that I want to point out. We personally surveyed our students that graduated a few years ago, from 2020 and 2021 start, and of those that replied, 100% of those are in paid work for an employer or engaged in the course of study, training or research. Two of the students that started then are doing PhDs with me. And also, a larger study that the government does, the postgraduate Graduate Outcomes Survey, this is for all of our masters courses from 2017 to 2022. 95% of our MSc graduates are in a graduate level job or further study.

Thanks Ed for the presentation, really insightful and useful. We'll now get onto the Q&A section of the session.

Q: Can you share a little bit more about the options available for the summer postgraduate project, please.

A: The way that the advanced research and development project works is that there are three types of project. There could be an academic proposed project. This is where me and my colleagues basically write a list of projects that we're working on, or projects that we're interested in working on with students. Students can then apply for that and have a chat with us and then be supervised over the summer, to work on that particular project. Also, we can have student proposed projects. This is where a student has a particular passion or interest, or a particular focus that perhaps will help them get a job after the course. So again, they chat to a potential supervisor for that project. They're then steered into how to make that into an academic project and then are then supervised as well. So as well as are these coming from us, they could be ideas that come from students as well. We also have industry partners or partner organizations that can propose a particular project as well. And again, there will be a list of those that then students can apply for. So that's not necessarily working day to day with that organization, that's where you are working on a problem that they have set and they kind of acting then as the client, there will be interaction with them, but it's not as though you'd be, going in there 9 till 5.

Love that, thank you, and nice to know as well that there's input from the postgraduate student.

Q: What type of placements are available? And a little overview of how people can get in touch with our placement support team.

A: So we have a number of academic staff that kind of act as a link and there's also somebody that works in collaboration with the school and the placements team. So their job really is to advertise roles when they come up. It could be the case that if a student has a bigger organization that they want to target, we could help with that, as well. Types of roles, so students have been placed as AI developers, support analysts, data analysts, research interns, data science interns, front end development and data analytics, data analysts for HR, and also app developers as well. So there's a range of different roles that students can kind of explore as part of this.

Really good to know there's that dedicated support there and a lot of varied placements as well. It sounds fantastic. Thank you for that Ed.

Q: What does the job market currently look like for graduates in in AI and Data Science?

A: It's, rapidly shifting. So I describe it as a shifting job landscape. So some of the roles our graduates going into even 2 or 3 years ago perhaps don't exist in the same way anymore. But there are still roles out there because AI and Data Science are still of the number one topics in the news, of course. There is still growing demand for roles like AI engineers, machine learning engineers, data engineers, prompt engineers. This is a role that wouldn't have existed 2 or 3 years ago that now is becoming more and more prevalent. And I suppose they're now overshadowing traditional data science postings that students would have been looking at 2 or 3 years ago. I think employers now expect graduates to be familiar with gen AI tools, and have AI literacy, knowing what machine learning is, data engineering. I suppose one of the interesting things, and this is why we've put it into the course, there is growing demand roles in AI ethics, safety and bias mitigation. So it may not be something that you think is obvious, you may think it's just all technical, but actually making sure that these things work safely, effectively and ethically is important as well.

Q: Can we just break down lovely the prior work experience required? Where does that entry requirements scope sit please, Ed?

A: What we’re primarily looking for is someone with a degree, and that degree can be in any subject. We're not looking for prior work experience in the area. But if a student doesn't have a degree but has some relevant work experience, then we'd look at that as well. We are generally open to applicants from any previous degree as well. We have had students from Humanities, we've had people that have come from nursing that are wanting to change their role in the NHS, and try and do something different.

Q: Would it be suitable for somebody who already holds a degree in computer science?

A: My suggestion would be if you're interested in this particular course look at the content. Computer science degrees across the world are all different, every university has a slightly different take on computer science. My real suggestion would be have a look at the course content on the website and start to see is there overlap, and are you happy with that overlap. Some students are, for example, our students have learned Java programming but not been taught Python programming, so they have the underlying skills, but want to learn a new programming language. It's very much dependent on the course that you've done. If you're unsure how much overlap there is then all you need to do is just give me an email.

Thanks Ed, and on our course pages, we do list and modules and detail as well. So that's the place to go and have a look at that.

Thank you Ed, I really enjoyed the session.