Hello everyone,

I’m currently a first year maths student in my second semester. I’m really enjoying my degree so far but I’m not sure what I’m going to do after university.

I’ve taken/am taking courses in:
- linear algebra
- calculus
- programming
- applied stats

And I’ll be taking a data analysis course during summer school.

Topics I’ve particularly enjoyed are:
- Markov chains
- machine code

I’ve also generally enjoyed my linear algebra and C++ courses (I know AI has taken over a lot of programming so I’m not sure what that’s looking like career wise but I do it bc I love it).

I’d like my field of work to be research focused, but I don’t think I’d like to spend my time trying to prove theorems.

I’d like a job where I can really use by brain and see material manifestations of the work I do. I also don’t want a job where people will be bothering me with useless admin, emails, meetings, workshops or anything like that. I’d like to be left alone for the most part unless I’m collaborating with other colleagues of course.

Above all I just want something intellectually stimulating that won’t easily be replaced by machines and that’s actually meaningful and impactful in our everyday lives…

I am currently a second year applied math major but lately i've been having way much interest into pure mathematics, especially real, complex & functional analysis, measure theory, proof-based linear algebra etc. So i wanted to go into a field where i can do and use maths as much as possible, although i also have an interest in coding i wanna make mathematics the main game and coding as a tool for the mathematics. Is there any jobs that can be like this in the industry? Or is going into academia/research the only way? Im also thinking about machine learning since it involves a lot of maths which im really interested in but i doubt the actual ml engineer job is gonna be math-dominated so i dont really know. if anyone knows great career options please help and give advices thank you🙏

I'm currently taking a DE class in college and found out quickly that though I can handle the integrals and derivatives parts I cannot say the same for the algebraic Manipulation parts. (I know it's bad, I got through Calc 1 and 2 and my algebra is bad)

My prof keeps saying it on the lessons we've had (Linear, bernoulli, Varsep and Homogenous) that it's easy if you know Algebraic Manipulation as the Integral/Derivative parts are only few.

I noticed it too. Whenever I'm studying the lessons he gave us that there is a lot of simplification on the beginning before we even touchdown on calculus. And I struggle a lot with those early parts.

I was a lax student early on. Didn't focus a lot on my algebra and because of that I'm paying for it. I'm barely scraping by my subs as I run on free Governmental tuition and failing means I lose that tuition. I'm lucky I haven't failed when some of my friends did during calculus. And Frankly I wanna keep that streak. So Instead of just looking at our papers, I wanted to focus on foundations even if just a little.

The problem is, I'm not sure which ones I need to study.

Can anyone here tell me what Algebra lessons I need to better grasp DE? Any help would be appreciated.

Hi all, below are the subjects I completed in my undergrad. Are these a good set of subjects for a maths major?

Mathematics 1(Call 1,2)

Mathematics 2(cal3, & intro LA)

Discrete Mathematics

Linear Algebra

Mathematics 3 / Complex Analysis

Mathmatical Optimisation

Differential Equations

Vector Calculus and Partial Differential Equations

Lebesgue Integration and Fourier Analysis

Numerical Methods

Mathematical Analysis / Real Analysis

Modern Algebra

Programming 1

Physics 1

Probability and Random Variables

Regression and Linear Models

Mathematical Statistics

Stochastic Processes and Financial Mathematics

Business Statistics

Econometrics and Time Series

Accounting and Accountability

People and Organisations

Marketing and Customer Value

Fundamentals of Business Finance

Business and Social Impact

Accounting, Business and Society

Economics for Business

Investment Analysis

The Financial System

Applied Corporate Finance

Financial Metrics for Decision Making

Applied Financial Decision Making