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Nonlinear
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This is my first post here, so allow me to first say hi and introduce myself a little.
I'm currently a finishing Master's student in computer science with a prospect of PhD, but for certain reasons I am contemplating pursuing an undergraduate degree in applied mathematics.
However, I never was a mathematical prodigy. I only entered the local (city or regional level, can't remember) mathematical olympiad once and the results were dismal, as I didn't know how to approach those problems, and I didn't do particularly well in a local math contest either. I wasn't bad in standard classroom math - I got the equivalent of A's during most of my primary school years as the grade from the subject (except for one or two years I think), even though I did not consistently score A's from tests. I certainly had to work for the results, though. I didn't have problem solving creativity that is required for the contests.
This resulted in me fearing the subject up until high school, where I got interested in it, but still, the success was won with hours and hours of excercises, and even then I was able to occasionally make a numeric mistake or struggle with some more difficult textbook problem (usually in geometry :) ). I enjoyed the subject tremendously, however. I didn't bother with math contests at high school - due to the instilled fear and the fact that I had to put in a lot of effort (i.e., it did not come by itself) I thought the results would be largely the same. I liked the subject so much that I did not want to part with it entirely during my uni studies, though, which is the reason why I went to study computer science instead of psychology.
I did some stupid things during my undergrad - skipping lectures, not preparing regularly, taking more courses than what was manageable - so my math grades reflect this. But even if I didn't, I would still have to put in hours to get very good results; I learn math by solving piles of problems of increasing difficulty. My GPA from undergrad is quite average, even though it puts me among the 1/4 of the best students of the degree. The degree was more theoretically oriented (quite proof-based - computation and complexity, automata and formal languages, algorithm design, and of course math) and as a result more tough, but I don't take that as an excuse for my performance. I improved dramatically during my Master's, though - even though I still rank approximately the same, the GPA is much better.
During my studies, I took a course in statistical methods and fell in love with the field, especially after finding out that machine learning and data mining, fields that are not taught at our uni but fields I find very interesting, are quite related to that. Our uni offers a Statistics degree (under the applied math umbrella), which is essentially the standard math degree minus some standard math courses + loads of statistics and probability related stuff. Given some of the bad memories, however, I am afraid of pursuing the degree. One thing is getting the degree, and a completely different thing becoming an (applied) mathematician.
I am no math olympiad stuff. There are people around me that are. Plenty of them. They just look at the theory, or sit in the class, and understand it straight away; they can solve difficult problems quick and with little exposure to the material. They get top marks with little effort.
I have to sit down with the textbook and conquer the theory by re-reading it again and solving problems, plenty of them, and even then absolute success is not guaranteed. I just like the subject and its applications, and would like to be able to become good enough to apply math to solve problems and create new applications in computer science. Or get a creative enough job that actually utilizes the math and the theory to solve interesting problems.
Is natural aptitude to solve math contest problems required to study mathematics as a degree, and become reasonably good in the field? Do I have to be "mathematically gifted" to do well?
I'm currently a finishing Master's student in computer science with a prospect of PhD, but for certain reasons I am contemplating pursuing an undergraduate degree in applied mathematics.
However, I never was a mathematical prodigy. I only entered the local (city or regional level, can't remember) mathematical olympiad once and the results were dismal, as I didn't know how to approach those problems, and I didn't do particularly well in a local math contest either. I wasn't bad in standard classroom math - I got the equivalent of A's during most of my primary school years as the grade from the subject (except for one or two years I think), even though I did not consistently score A's from tests. I certainly had to work for the results, though. I didn't have problem solving creativity that is required for the contests.
This resulted in me fearing the subject up until high school, where I got interested in it, but still, the success was won with hours and hours of excercises, and even then I was able to occasionally make a numeric mistake or struggle with some more difficult textbook problem (usually in geometry :) ). I enjoyed the subject tremendously, however. I didn't bother with math contests at high school - due to the instilled fear and the fact that I had to put in a lot of effort (i.e., it did not come by itself) I thought the results would be largely the same. I liked the subject so much that I did not want to part with it entirely during my uni studies, though, which is the reason why I went to study computer science instead of psychology.
I did some stupid things during my undergrad - skipping lectures, not preparing regularly, taking more courses than what was manageable - so my math grades reflect this. But even if I didn't, I would still have to put in hours to get very good results; I learn math by solving piles of problems of increasing difficulty. My GPA from undergrad is quite average, even though it puts me among the 1/4 of the best students of the degree. The degree was more theoretically oriented (quite proof-based - computation and complexity, automata and formal languages, algorithm design, and of course math) and as a result more tough, but I don't take that as an excuse for my performance. I improved dramatically during my Master's, though - even though I still rank approximately the same, the GPA is much better.
During my studies, I took a course in statistical methods and fell in love with the field, especially after finding out that machine learning and data mining, fields that are not taught at our uni but fields I find very interesting, are quite related to that. Our uni offers a Statistics degree (under the applied math umbrella), which is essentially the standard math degree minus some standard math courses + loads of statistics and probability related stuff. Given some of the bad memories, however, I am afraid of pursuing the degree. One thing is getting the degree, and a completely different thing becoming an (applied) mathematician.
I am no math olympiad stuff. There are people around me that are. Plenty of them. They just look at the theory, or sit in the class, and understand it straight away; they can solve difficult problems quick and with little exposure to the material. They get top marks with little effort.
I have to sit down with the textbook and conquer the theory by re-reading it again and solving problems, plenty of them, and even then absolute success is not guaranteed. I just like the subject and its applications, and would like to be able to become good enough to apply math to solve problems and create new applications in computer science. Or get a creative enough job that actually utilizes the math and the theory to solve interesting problems.
Is natural aptitude to solve math contest problems required to study mathematics as a degree, and become reasonably good in the field? Do I have to be "mathematically gifted" to do well?
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