Online learning: from optics to AI
Andrei-Ioan Bleahu (MSc 2025) completed the online Masters programme in Data Science at St Andrews. He discusses his decision to study flexibly and remotely, his ambitions to transition into the field of AI, and the support he received from the global University community.
Studying for my Masters in Data Science online at the University of St Andrews broadened my horizons. Now that I have completed my postgraduate degree, I feel as though I am looking through a rear-view mirror: as I reflect on how far I have come, the road ahead comes into sharper focus.
Prior to matriculating at St Andrews, I completed an MPhys at the University of Southampton. I eventually moved into academic research and worked as a Junior Research Fellow in Physics at the University of Tartu in Estonia.
My field, experimental optics, was very hands-on and, perhaps surprisingly, had a lot in common with data science. From setting up experiments, collecting data, analysing results and extracting useful insights, experimental optics is a process of extracting meaning from complex signals.
Beyond experiments, the overlap between physics and data science sparked a bigger question for me: could I transition into data science, and eventually forge a career in AI?
My background is in signal processing and mathematics and I quickly realised that data science is no longer a ‘new’ field. To grow beyond the fundamentals, I needed a deeper understanding of modern machine learning and AI. As my first step in pursuing a career in data science, I began working as a freelancer within the industry. It was an exciting shift, which was helped by my physics background.
During this experience, I became aware of a gap in my knowledge. While I could analyse data confidently, I lacked the strong machine learning foundation needed to reliably design AI-driven solutions. I wanted to move beyond data analysis and into building models that could learn from data and generalise. This led me find and apply for the online MSc in Data Science at St Andrews.
Innovation in practice
The innovative field of data science was reflected in the programme at St Andrews, with its structure placing a strong emphasis on hands-on, applied work. We explored anonymised datasets, built reproducible workflows in Python and developed end-to-end machine learning solutions. This gave me real-world experience in ‘owning’ the entire data workflow: from defining the problem to communicating the results clearly.
What stood out to me most on the programme was the balance between theory and practice. In addition to learning theoretical concepts, we were taught how to apply them successfully and justify each modelling decision based on the dataset and the problem context. This approach helped build my confidence and develop skills that translate directly into practical data science applications.
Joining the global St Andrews community
Studying remotely as a mature student might sound challenging – and in many ways, it was. The programme required discipline, consistency and the ability to juggle my studies alongside work and other responsibilities. However, what surprised me most was how connected I still felt to the University community. Even from a distance, I never felt like I was studying alone. The tutors were friendly, supportive and genuinely invested in our progress. I was supported and encouraged at every step of the way; I knew I was part of the close-knit St Andrews community, despite being thousands of miles away.
Just as importantly, I learned alongside fellow students from a variety of different backgrounds – people with unique experiences, perspectives and professional goals who recognised the importance of data in their careers. Looking back, the programme did more than teach me data science. It expanded my professional perspective and gave me the confidence to pursue AI not just as an interest, but as a career path.
St Andrews wasn’t simply a step in my academic journey; it was a turning point in my life.