Why did you pursue MSc AI in the Biosciences programme?
Artificial Intelligence (AI) is tapping into every industry, and I was looking to upskill myself in this area. This programme was particularly interesting to me as I come from a biology background but soon realised, I enjoy analysing results and working with large data sets to arrive at conclusions rather than the practical Lab element. This course has been great as there has been an emphasis on hands-on experience and not just learning theory.
What have been your highlights so far?
A main highlight has been the opportunity to go through the whole machine learning process. This hands-on approach has prepared me for going into industry. In the first semester, we learnt how to code and took it from scratch which was helpful and made it less intimidating. I have also enjoyed thinking critically with my classmates and working with information to get to solutions.
Have you thought about any particular career paths?
I am still exploring different fields but machine learning and the automation of processes that I am considering. This programme gives you a lot of data and functional skills that can be applied in different areas such as pharmaceuticals, marketing, research. I have found that most sectors welcome students with a background in AI and machine learning. I have also enjoyed working in collaboration with Kew Garden on the plant species identification model, in the future AI could play a huge part in helping farmers identify disease on the leaves of their crops.
Can you tell us about your experience of QMUL?
I really like QMUL and the campus feel as it really caters for everyone. I studied for my undergraduate degree at a different university and have really enjoyed QMUL so far. I feel like I have learnt so much from my classmates as we are all from a diverse range of backgrounds so not only from different countries but from different professional backgrounds. These really makes group discussions interesting as new perspectives can be brought to the fore. For example, not everyone in my class is from a computer or a biology background and the programme also doesn’t require you to have any coding experience. There are lots of PHD opportunities on offer too which really highlights the research going on here.
How have you found the facilities?
Facilities very good, especially the Careers Service. They offer internships, career taster sessions, 1;1 appointments, and there is an online programme to look at your CV. I applied for an internship position back in January and got an appointment to go through my CV and cover Letter and then to prepare for the interview. The Career service was so helpful and made it a smooth process, being flexible at short notice. I was lucky enough to get offered the position of a Data Mining intern and I will be working with Good Mind, a start-up to build an app to help people be more sustainable by selling or upcycling products. I will be monitoring data and looking at data from competitors to see what is around etc. One of the people at the company is also a QMUL Graduate.
Have you any tips for those starting this programme or at Queen Mary?
Be curious – as questions and explore topics beyond the scope of the course to get a deeper understanding Relies on you to be a bit proactive. Be curious and grasp opportunities – go along to part-time job fairs. Take advantage of all the resources on campus such as the Careers Service. Also the language learning courses are great and very accessible.
What do you think about the teaching and your lecturers?
The course is quite small, and this means the lecturers can really get to know you. The lecturers really care about the student experience and don’t just give you feedback but check in with you about the course content. I feel heard as class feedback has been taken on board. For example, we asked if one of the lecturers could take it a step back with the maths content as many of us hadn’t studied maths since school. The lecturer broke the content down and offered more support. It really does feel like a more two-way relationship compared to undergraduate where students can ask more questions and give greater input but also question things a lot more.