With a background in Business Mathematics and Computer Science, and many years of experience in Tactical Asset Allocation, I joined this programme to refresh and enhance my understanding of applied AI. What appealed to me most is that it moves beyond traditional linear models, financial markets are inherently non-linear, and the advanced techniques taught here capture that complexity far more effectively.
I especially value how directly applicable the content is. Machine learning and neural networks can help identify patterns in alternative data sources that humans might overlook, thereby supporting more informed asset allocation decisions. At the same time, I believe the future will remain hybrid: AI complements human expertise rather than replacing it.
The fact that the programme is offered by a well-known university, with instructors closely connected to the latest academic and practical developments, made a real difference. My advice to future participants: make sure you have basic Python skills and be prepared for mathematics.
Aart is a Portfolio Manager Multi-Asset and completed the Data Science in Python program in 2025.
