Hi guys. So basically the title here, I’m about to start my undergrad and struggling between choosing these three as a second major after pure maths (my uni makes you do two).
Let me give a brief summary of each course.
Applied maths: the first two years of applied maths modules that aren’t physics or modelling related, I.e. the traditional ones like ODEs, PDEs etc are easily to include if I do pure maths anyways, so if I don’t pick this as a second major I’m mainly missing out on courses on mathematical modelling and computing, non-linear dynamics, boundary value problems and numerical analysis.
Overall this seems like it would be a fun major and I can include computer science upto a second year for CS students and I can also include mathematical stats upto a second year for maths stats majors.
The downside in this selection is that the applied maths course has a lot of physics especially in the third year which I don’t know if I’m keen on. Feels like too many credits are in physics over the course. Apart from that I really enjoy applied maths type problems with calculus and stuff like that so I think I could thrive in this major.
Mathematical stats: mathematical stats is supposed to be an ultra difficult and has a very high failure rate throughout the years and even in the first course/module. It is a weirdly low credit major though and so if I pick this I will have a lot of freedom with electives in CS and applied maths, up to the second year again.
This major is the closest to an extension of pure maths in terms of its rigour and difficulty/abstractness. But you also learn how to use R and it even includes a course on “statistical modelling, machine learning and Bayesian analysis” in the last year which is half your credits for that year. The other half of the last year is an introductory stochastic calculus course. Linear models are included etc.
This would be a good major in my view as it’s known for being extremely hard. I’m not the biggest fan of high school stats but I like how the modules at least start from a mathematical point of view before progressing. It also covers the stats I would need for actuarial science which I could pivot to incase I change my mind or I don’t get in. My main thing with this is I’m likely to perform a bit worse and be a little more busy in uni with this selection than with the applied maths.
Computer science: the CS course is more of a software dev/engineer pipeline. I’m not really sure I want to major in it for this reason, it’s not very theoretical, mathematical and rigorous. On the plus side though there are many projects which would force me to learn how to code decently. There is some machine learning stuff but it’s more general to computer science as a whole than directed at modelling. This feels like it would be a waste of time the third year courses which I would miss out on with one of the other selections are on operating systems, computer networks, advanced software design and algorithms. If I ask my uni maybe I could do this as a third major since I know some students do three but that will be really difficult. There is a course on C++ and machine learning in the last year which would be great to know.
So a lot of writing I know but I didn’t want to leave anything up in the air. If anyone can respond that would be great!!!
Let me give a brief summary of each course.
Applied maths: the first two years of applied maths modules that aren’t physics or modelling related, I.e. the traditional ones like ODEs, PDEs etc are easily to include if I do pure maths anyways, so if I don’t pick this as a second major I’m mainly missing out on courses on mathematical modelling and computing, non-linear dynamics, boundary value problems and numerical analysis.
Overall this seems like it would be a fun major and I can include computer science upto a second year for CS students and I can also include mathematical stats upto a second year for maths stats majors.
The downside in this selection is that the applied maths course has a lot of physics especially in the third year which I don’t know if I’m keen on. Feels like too many credits are in physics over the course. Apart from that I really enjoy applied maths type problems with calculus and stuff like that so I think I could thrive in this major.
Mathematical stats: mathematical stats is supposed to be an ultra difficult and has a very high failure rate throughout the years and even in the first course/module. It is a weirdly low credit major though and so if I pick this I will have a lot of freedom with electives in CS and applied maths, up to the second year again.
This major is the closest to an extension of pure maths in terms of its rigour and difficulty/abstractness. But you also learn how to use R and it even includes a course on “statistical modelling, machine learning and Bayesian analysis” in the last year which is half your credits for that year. The other half of the last year is an introductory stochastic calculus course. Linear models are included etc.
This would be a good major in my view as it’s known for being extremely hard. I’m not the biggest fan of high school stats but I like how the modules at least start from a mathematical point of view before progressing. It also covers the stats I would need for actuarial science which I could pivot to incase I change my mind or I don’t get in. My main thing with this is I’m likely to perform a bit worse and be a little more busy in uni with this selection than with the applied maths.
Computer science: the CS course is more of a software dev/engineer pipeline. I’m not really sure I want to major in it for this reason, it’s not very theoretical, mathematical and rigorous. On the plus side though there are many projects which would force me to learn how to code decently. There is some machine learning stuff but it’s more general to computer science as a whole than directed at modelling. This feels like it would be a waste of time the third year courses which I would miss out on with one of the other selections are on operating systems, computer networks, advanced software design and algorithms. If I ask my uni maybe I could do this as a third major since I know some students do three but that will be really difficult. There is a course on C++ and machine learning in the last year which would be great to know.
So a lot of writing I know but I didn’t want to leave anything up in the air. If anyone can respond that would be great!!!
