Best mathematics courses to study in preparation for a tertiary degree in mathematics Whilst this question can potentially be considered off topic I still believe that it is relevant and can benefit the site as a whole.
I've recently completed all of the mathematics courses in my school and still have a keen thirst for more knowledge as I really enjoy mathematics. I'm looking to pursue a dual degree of mathematics and computer science as an undergraduate degree for university, with a large focus on machine learning and it's applications. Whilst not entirely sure I think i'm leaning towards majoring in applied mathematics.
The topics that I've completed at school are:
Arithmetic and geometric sequences, functions and graphs, counting and probability, logarithmic and trigonometric functions
Calculus - Differentiation of continuous functions using the chain, product and quotient rule, Basic integration using U - substitutions. We've also covered basic applications in a 2 dimensional sense such as optimizing variables such as time.
Probability - Normal distributions, probability density functions, binomial distributions, sampling and estimation, confidence intervals.
Obviously my undergrad degree will be quite math intensive, but there is about 6 or so months until that starts and I don't think I can go that long without learning any new topics.
So, my question to all experienced mathematicians out there is: What are some math topics I should learn in preparation for studying mathematics and computer science at university?
Many thanks in advance.
 A: I think not the topic itself but the thinking in university is more important to learn. Math at school is completely different than math at university. You're proving so many things, in school you only apply some formulas.
However, I really like Algebra and I think that this is the best point to start with. You learn basic concepts (groups, rings, fields) and getting used to math notation, proofs and the mathematical thinking which is necessary to get a degree in maths.
For Machine Learning especially Analysis is of greater importance, but IMO this topic is harder to understand for a beginner than Algebra is. One reason is that in Algebra you can sometimes draw, but in Analysis you often work with infinity or infinitely small things which is not easy to handle (at first). I would really concentrate on getting this mathematical meta-skills how to proof things to prepare for university.
It depends on your interests. If you want to visit some lectures, you should have a look at MIT. All courses are publicly available and have high quality.
