

How should a BSc Computer Science student choose between an MSc in CS, Math, or Stats to build the strongest mathematical foundation for a future PhD?
I am currently pursuing a BSc in Computer Science, but I want to build a much stronger mathematics foundation leading all the way up to a PhD to enhance my problem-solving skills.
The university where I plan to pursue my MSc requires 60 total credits. The program structures differ by field:
MSc in Computer Science: A full 60-credit dissertation.
MSc in Statistics or Mathematics: 30 credits of coursework (10 modules at 3 credits each) and a 30-credit dissertation.
During my BSc, I have already completed Linear Algebra 1, Calculus 2, Discrete Mathematics, Formal Methods, Introduction to Probability, and Data Structures & Algorithms (DSA).
I have room to take elective modules in my final year: two in Semester 7 and one in Semester 8. The available options are:
Semester 7: Linear Algebra 2, Calculus 3, Basic Statistical Theory 1, Fundamental Concepts of Algebra, and Numerical Analysis.
Semester 8: Advanced Algorithms (follows DSA), Real Analysis 1, Ordinary Differential Equations, and Statistical Theory 2 (requires Statistical Theory 1).
My final elective choices will largely depend on which MSc path I choose. Because of this, I have a few questions:
Which path would you recommend I pursue: MSc CS, MSc Stats, or MSc Math?
Based on your recommendation, which specific BSc modules should I select for Semesters 7 and 8?
If you recommend opting for the MSc in Stats or Math, could you help me select the best 10 modules to take from their respective curricula?
Career-goals: I don't know what I want but only that I want to be a problem-solver that uses I love math and tech, even better, if it's R&D.