I chose to study the MSc in Machine Learning for Visual Data Analytics (MLVDA) at Queen Mary University because of my growing interest in machine learning, particularly in computer vision. After several years in data engineering, I frequently encountered machine learning applications and realised that I wanted to transition into this field professionally. However, I knew that mastering these concepts would require more than self-teaching, as most roles I was aiming for required advanced qualifications. Queen Mary stood out to me due to its strong reputation in computer vision, and the opportunity to study with leading experts made it the perfect choice. Modules like "Introduction to Computer Vision" with Andrea Cavallaro and "Deep Learning and Computer Vision" with Sean Gong were especially impactful, as both lecturers were exceptionally knowledgeable and engaging, deepening my passion for the subject.
The most valuable aspects of the MSc programme were the practical skills I gained in machine learning and computer vision, as well as the experience of conducting research, designing experiments, and critically analysing academic papers. My research project was a major highlight, particularly the video presentation I created as part of it. This presentation played a crucial role in securing an interview, which ultimately led to a job offer as a Computer Vision Engineer at Hawk-Eye. Although I didn’t join any societies or attend industry events during my time at Queen Mary, the knowledge and experience I gained from the programme had a significant impact on shaping my career.