Why study artificial intelligence? How to break into AI | with the University of Essex Online 

In this episode, we chat with Sharon Sibanda, head of computing at the University of Essex Online, about the MSc Artificial Intelligence. Sharon shares how the course equips students from all backgrounds with the skills to thrive in the fast-moving world of AI

Participants

• Emily Slade - podcast producer and host, Prospects
• Sharon Sibanda - head of computing, University of Essex Online

Transcript

Emily Slade: Hello and welcome back to Future You. The podcast brought to you by graduate careers experts, Prospects. I'm your host, Emily Slade and in this episode I chat to Sharon Sibanda from the University of Essex Online about their MSc in artificial intelligence.

Sharon Sibanda: Hi so my name is Sharon Sibanda. I am the head of computing at the University of Essex Online, which is run by Kaplan open learning and my area of expertise is artificial intelligence and the specific area that I'm interested in is how artificial intelligence relates to learning learning outcomes particularly in the subject area of computing at various levels.

Emily Slade: Perfect. Well, thank you so much for joining us. So we are here today to talk about the MSc Artificial Intelligence. So can we start if you're able to tell me a little bit about the programme?

Sharon Sibanda: This programme is really exciting. It focuses on the principles, the technologies and the practises of AI, artificial intelligence and what we hope is that students will gain a really good foundation in those key aspects and it will give them the right skill set to be competent practitioners in this. Really fast-paced and ever changing environment in the area.

Emily Slade: Yeah. Perfect. So why has this programme been created?

Sharon Sibanda: Right. So we've looked at programmes which are actually existing and we feel that there's a gap for a programme which is a generalist programme, so it's a conversion degree and it's a masters degree which is aimed at graduates from any discipline who are looking to move into the field of artificial intelligence. Or even those who are working in it in business and are looking at converting to this particular area.

Emily Slade: Perfect. So who who is the programme aimed at?

Sharon Sibanda: It could be existing researchers who want to perhaps switch across to artificial intelligence as it becomes more important in their industry. It could be people who are working, who are maybe in particular, maybe they're in IT or business and they're looking to develop. Career and artificial intelligence is an area that they're looking to get into. It could be. Senior managers, middle managers who are also looking to get a better understanding of artificial intelligence and how they can use it for decision making. So it's anyone really who has a passion or an interest in the area. And who's looking to perhaps convert from a different area, or who has been involved in in IT and computing in a different discipline and are looking to further understand this specific discipline.

Emily Slade: I suppose a lot of industries are now having to deal with artificial intelligence. It's making its way into almost everyday life, so this course really sounds like it could be open to anyone with an interest, regardless of your background or industry.

Sharon Sibanda: Yeah, that's right. The idea here is to give everybody a necessary technical expertise, give them insight into some of the specialist area. That would help you to understand how you can apply it in your particular area and just to give that creativity as well around how you might actually start becoming creative when it comes to AI based solutions and how they might apply to a commercial or practical problem.

Emily Slade: Absolutely. So it can enhance people that are already comfortable in their career, working in their job, but also what career opportunities are available to graduates who complete this programme.

Sharon Sibanda: So this is really interesting actually, because I think the idea is you should be able to either design, integrate, deploy or use AI powered solutions. So the kinds of career opportunities are ever changing. Most recently there are roles such as an AI engineer or a senior AI engineer. There are roles around AI and ML engineers, AI, solution architect. AI integration specialists, as we've mentioned, this is actually now cross discipline. So those kinds of roles are across multiple teams in an organisation. Web developers who are looking to be AI trainers, consultants, AI researchers and even senior applied scientists.

Emily Slade: Yeah, fantastic. So can you run us through the key modules of the course?

Sharon Sibanda: We will be offering seven modules for the MSc in AI and the first module is the launch into computing. And this module focuses on cross disciplined concepts such as understanding, risk, understanding, basic foundational computing concepts, and considering areas of ethics. The next module would be understanding artificial intelligence, where the role of AI in society is explored. The ethical and safety issues in AI are also looked at. Numerical analysis is another module, and this module focuses on the key mathematical and statistical concepts and techniques that actually underpin data science and AI. And of course, importantly how you would use these concepts for decision making. Another module is machine learning. Machine learning looks at understanding how we would apply machine learning algorithms to different data sets and to challenges that are faced in the real world. And what's important is to actually be able to critically appraise exactly which machine learning algorithm to use in which particular way. So the idea of technical risk and uncertainty is involved in that kind of decision. So it's important to be critical in in appraising which machine learning techniques. You would actually utilise for real world problems. Intelligent agents are another module that is looked at, so agents are software programmes that can understand their environment and they actually act in a way that helps them to achieve a desired goal. So this module is focusing how those agents are actually developed, the different architectures and approaches to them. And actually analysing their effectiveness as well. The last two modules research methods are where we're looking at understanding how you can qualitatively or quantitatively approach research or even use mixed approaches. And the computing project is the one of the final modules where as I mentioned before, it's it lasts a bit longer than the others and it's aim really is to help students to focus on some action research and then they can use public data sets or they can generate data. With the permission, even undertake a proof of concept within an organisation so that they can investigate a specific AI based approach.

Emily Slade: Fantastic. That's brilliant. Thank you. So what would you say are the standout features?

Sharon Sibanda: While thinking about some of the modules for understanding artificial intelligence, the most interesting part of of of that specific motto is how students will be given an opportunity to investigate. Recent research around AI and more importantly, kind of explore the ethics. Of some of the AI systems that are being considered that are being that are already out there in some depth. For intelligent agents, I think students will find it really interesting that they'll be able to collaborate with their fellow students and actually perform an exercise where they develop an agent that will be performing tasks in a specific domain for machine learning, I think. For most learners, understanding how to apply machine learnings and machine learning techniques in the 1st place is quite important. But then we need to move on to the more complex bit which is evaluating their effectiveness. Understanding which metrics to use when, and then investigating some recent trends around industry 4.0, for example. So we've got edge AI at the moment, which is looking to enable real time decision making. But using low powered devices. So that's one of the the recent trends that could be a focus and another recent trend that could be a focus is also neural architecture search, which is looking at automating deep learning model design as part of the this particular module. Finally the major project. In itself is a highlight, I would say of the programme as well, because it helps students to actually focus on a project. You can then do a deep dive into an area of interest. As previously mentioned, you might want to develop a proof of concept. And for career opportunities, that's a good way of actually showcasing your skills and your knowledge and even developing something which may be parallel to what your organisation does by using either a public data set or generating your own data. These are some of the the the things that can be accomplished within the major project.

Emily Slade: Fantastic. So what are the entry requirements for this programme?

Sharon Sibanda: So there are probably, I would say two main entry routes. We've got the academic entry route where you would require an undergraduate degree from an approved institution, which is equivalent to a UK honours degree or a relevant professional qualification. But you also have the work experience route because we don't want every anyone to be left out. And here if you have at least three years IT computer science work experience, even business experience, then you will be considered. There are some aspects to consider when it comes to English. So if English isn't your first language, then you would require the IELTS (International English Language Testing System) pass, an equivalent of a 6.5, but you don't need to prove your knowledge of English. If you're a UK national or your qualification equivalent is, your qualification is equivalent to a UK degree. There's also the open route and the open route here. I mention it because that is by case by case basis, so if you're really interested and you have done some work around AI, and perhaps you have some other certificates which don't quite fit either of the the the two that I've mentioned, the academic entry route and the work experience route. You can certainly apply and look to see if the open route might be available to you.

Emily Slade: Excellent. And finally what what is the most exciting thing for you about this course?

Sharon Sibanda: I think it's the the way that the course allows students to develop their understanding. Their critical understanding of such an important area. AI has become so pervasive now that it's really important that students are. Kind of familiar with the developments. That are ongoing and because it's so fast-paced as well, we're really excited that we're able to continue to adapt and change the modules according to the developments in industry. So it's really exciting to be able to offer such a course where recent trends can be looked at. I mean, industry 5.0 is coming up. And so we're really excited. To you know, encourage students to join the programme and maybe learn a little bit more about what industry 4.0 is and what industry 5.0 is all about and where that's taking. Artificial intelligence in particular.

Emily Slade: Yeah, definitely. And if anybody listening wants to get in touch with you to ask any further questions about the course, are they able to do?

Sharon Sibanda: That, yeah, absolutely. So my details will be in the show notes below, and yeah, we'd love to hear from anyone who's interested in the programme.

Emily Slade: Perfect. That's brilliant. Well, thank you so much for your time. Today.

Sharon Sibanda: Thank you so much Emily.

Emily Slade: Thanks again to Sharon for their time For more information on the course, check out the show notes below. If you enjoyed the episode, feel free to leave us a review on Apple or Spotify. Thank you as always, for listening and good luck on your journey to future you.

Notes on transcript

This transcript was produced using a combination of automated software and human transcribers and may contain errors. The audio version is definitive and should be checked before quoting.

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