Why you chose to study at RGU?  

The reasons I chose RGU were the academic standing of the institution, the standard of its courses and facilities, the campus's setting, the resources, and support services offered to students, the availability of research opportunities or internships, or the university's inclusive and diverse student body and faculty. Another reason was the quick and candid responses from the school office all queries were addressed in a timely manner.

The computing school at RGU is fille with resources and resource people who will guide you to the best of their ability.

Highlight of my degree?

A unique feature was the approachability of the Academic staff. In all my modules the tutors were extremely friendly and thoughtful and gave the correct guidance depending on the stage we were in at the time. The warm approachable nature of the academic staff was the key reason I completed this master's program. My course leader (Dr David Lonie) and my course strategic lead (Dr Ines Arana) were always there when I had questions and needed guidance.

How will my degree support career and future goals?

My goal is to become an eminent data scientist soon. The RGU curriculum armed me with the theoretical and practical skills I needed to compete in the challenging data science industry. The course was holistic and covered many important and novel areas useful for a modern data science practitioner. I am currently putting the skills I honed throughout the course to build production-level data science solutions.

Any tips or advice for future students?

My advice to future students is to be proactive. Complete all lab sessions at the first opportunity and always question how the concepts or skills you learn will help you when you work industry or conduct research in academia after your masters. Another tip will be to use the drop-in sessions to your fullest benefit. It’s very important to have one on one chats with tutors and question any unclear elements in each module. I will you all the best.

The first semester will be hardest since you need to get used to the delivery methods and cope us with the requirements for the first time. It’s also important to complete all the assignments as soon as they are released so that you can keep the weekends free for exam preparation activities. Try to proactively cover the material and keep the lecture delivery session as an opportunity to ask questions and clarify any unclear areas.

No matter what you do there will be times that you will feel bogged down with the work and hectic the way I learned to cope with when it got like that during my master’s was visualizing myself completing the master’s and walking across the stage on graduation day.

Organise group study sessions with friends and discuss ideas and compare notes this will help you gain a broader understanding of data science. Last tip is master cloud technologies (AWS, GCP, MS Azure, Kubernetes, or Docker) whilst studying for the masters especially if you are inclined to work in the industry post-graduation.