Is brilliant org better than khan academy
Long term attack plan to learn math? [closed]
I am a web developer with a desire to expand my knowledge of programming-related math.
As a 2nd career, I'm stuck in college and doing some of the requirements on the job.
I was hoping my education would teach me the skills needed to use math, but I quickly discover that it is too inefficient for the time invested.
For example, in my Calculus 2 class, volumes and areas under the curve were the only things that helped me expand my knowledge. The rest was just monotonous, glorified algebra that I find easy, but can be done in seconds with software like Wolfram Alpha. This is not my idea of learning math.
So here I am a frustrated student looking for a way to improve my understanding of math in a way that is focused on applying, understanding, and eliminating unnecessary boredom as much as possible.
However, I cannot find a good long-term study strategy for this approach.
So how would you go about it for like-minded people to learn the math without worrying about things that a computer can do much better?
Read Steve Yegge's post on Mathematics for Programmers.
To his insights:
Math is a lot easier to learn after you know how to program. In fact, if you're a halfway decent programmer you'll find that it's almost a no-brainer.
You teach math the wrong way in school. Way, way wrong. If you teach yourself math the right way, you will learn faster, remember it longer, and it will be much more valuable to you as a programmer.
If you know even a little about the right kinds of math, you can write some pretty interesting programs that would otherwise be too difficult. In other words, math is something you can learn whenever you have the time.
Nobody knows math, not even the best mathematicians. The field is constantly expanding as people invent new formalisms to solve their own problems. And for any given math problem, just like programming, there is more than one way to do it. You can choose the one you like the most.
Math is ... actually a bit of fun if you do it right.
You can tell the difference between mathematics and the math they teach you in school .
This is done in A Mathematician's Lament described excellently by Paul Lockhart. Conrad Wolfram expressed something similar in his TED lecture " Teaching Kids Real Math with Computers ” .
Most of the math you need in "life" was taught in elementary school (how to calculate a tip in your head). The math you use in your job will possibly Taught by your university if you're entering a subject that requires calculus or other advanced math - but most programmers don't use calculus on a daily basis (since most programmers end up writing business applications, no engineering).
Regardless, a lot of the math you learn won't apply to you. And a lot of what you do while you study is calculation. Will it ever be fixed? It is up to you and the rest of your generation (and all future generations) to decide.
I'm in a similar boat and so far enjoy www.projecteuler.net:
The Euler project aims to encourage, challenge and encourage everyone who is interested in the fascinating world of mathematics.
They are problems that you solve by programming, but most problems are aimed at teaching you certain math (or you have to learn first) in order to solve them. Helps in learning math skills that you can apply while programming.
Another great resource is http://www.khanacademy.org/#calculus
KhanAcademy is much more than just brilliantly made videos, it also has a whole practice system to test you out. See http://www.khanacademy.org/about
They don't mention what type of programming you're doing or what you're interested in. If you are into computer science you need this calculus background, every 3 semesters, linear algebra, differential equations, numerical analysis to name a few. You will also need all the requirements for science, physics, biology and chemistry. There is another branch of applied mathematics in communication systems theory. There you will learn number theory, algebraic coding theory, cryptography, mathematical aspects of systems theory, applied Fourier analysis and probably others.
If you're interested in databases like me, I'm studying Applied Mathematics for Database Professionals. Once I'm done with that, I'll tackle anything I like, probably something from CJ Date, and set and group theory.
To answer your question on how to develop a curriculum, do your research at various universities and see what they offer in the fields of computer science or applied mathematics. Universities publish the requirements for the degree. You can probably find all courses online, usually with videos, problem sets, and you can probably find the book on Amazon. MIT has Open Courseware, Harvard and Berkeley also have online courses. Also check out OpenStudy. There may be a study group set up for the class you want to take.
If you need the knowledge and don't want to go into debt for a Masters, self-study is a great way to go.
If you want to do algorithms in general, finite math and abstract algebra courses should help (or you can just take an algorithms course ...). Finite math also helps with coding, encryption, and a variety of other areas of computational algorithms. You should try to take a look at Knuth's The Art of Computer Programming, if only as an indication of the kind of math you might find useful.
If you want to do number processing (the kind of thing your calculus and linear algebra use), check out the latest edition of Numerical Recipes. I also recommend Golub & van Loan's matrix calculations as a more mathematically correct text on linear arithmetic algebra.
In general, if there's an application domain you're interested in, head over to the library and peruse some books on the subject to find the kind of math that they need. There may not be a dedicated course on the subject, but don't let that stop you. The ability to identify and learn a store of knowledge on your own initiative is one of the most valuable skills you can acquire: if this were the only thing you learned in school, your time and money would still be well spent.
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