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On March 11 2012 05:48 KurtistheTurtle wrote:
I'm thinking: All the statistics courses available and matrix algebra. Maybe it's linear algebra?
Matrix algebra is like the first 3 chapters of an intro Linear Algebra course.
I do agree that KhanAcademy is a great website especially if you want to fill all of your holes in Math. Combined with the exercises and videos, you should be able to achieve mastery up to Calculus I, or at least that's the claim.
Applied Statistics has a lot less theory involved and more application, so if that's something that you're interested in, then definitely go for an intro Applied Statistics course.
There are also occasionally different types of Linear Algebra courses in University i.e. ones that stress computation, and ones that are pretty much purely proof-based and more abstract, so choose wisely if your school offers multiple options.
Linear Algebra is very useful, but I do agree that it is quite painful overall, and I'm never taking another Linear Algebra course beyond my intro one.
In terms of recreational math, there's a course called Joy of Mathematics from Arthur Benjamin, which is pretty cool http://www.thegreatcourses.com/tgc/courses/course_detail.aspx?cid=1411
Although I am liking his Secrets of Mental Math course a lot as well.
You can buy them or possibly find them illegally on torrents if you're into that sort of thing.
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On March 11 2012 05:48 KurtistheTurtle wrote:
I like the part of math where I can take a process, quantify all the interrelated variables, then manipulate numbers to reveal insights or realities which aren't immediately obvious. Find the pockets of value where intuition fails. I hated statistics when I took it (because of the teacher...and the fact it was "math at school") but recently I've been helping my gf & another friend with their homework. When I can manipulate numbers to arrive at an answer, I feel like a boss. If I could do this to massive data sets and provide insightful, relevant and useful insight & information...that would get me up in the morning. In the coming years, many amazing things will come out of the proper analysis & communication of the MASSIVE amount of data now available.
I'm the guy who's naturaly predisposed to do just that. I like internalizing large amounts of information, figuring it all out, finding the valuable advancement or achievement of a particular goal, then moving on to the next thing. I also like spending lots of time alone and not being disturbed. I also love focusing on one particular, giant, intricate problem. This is the skill I want to cultivate.
I don't know what its called though. Applied statistics, "big data" analysis, etc.
What are the classes I should take centered in this area (undergrad or grad)?
I'm thinking: All the statistics courses available and matrix algebra. Maybe it's linear algebra?
Also, I was looking into HADOOP. What other related stuff should I learn? (learning HTML5 already, so what else?) Basically marketable applications of the theoretical stuff I learn so I can apply it right away and stay excited.
Linear algebra will come in handy if you're going in that direction, some statistic subjects might even list it as a pre req.
Also have a look at: http://en.wikipedia.org/wiki/Mathematical_statistics
Some places will give out those types of job to any CS or maths major but it varies by country and who your competing against. They generally do analyst etc under a guideline set by the company.
If you want to actually create the models for these people you're going to have to get a PhD... CS uses a lot of statistics but I'm not sure about qualifications in that field.
EDIT: O yea you might wanna look at SAS.
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lol, loving this thread. Math maybe the course I struggled the most with, having fun in several of the links provided, just started at the Khan academy, it looks awesome.
Is there any sites similar to that for learning how to write awesome??
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On March 12 2012 15:56 ImDrizzt wrote:
lol, loving this thread. Math maybe the course I struggled the most with, having fun in several of the links provided, just started at the Khan academy, it looks awesome.
Is there any sites similar to that for learning how to write awesome??
Did you even read my other post :/. The materials there are divided into university year levels. Aside from general stuff like geometry results, you don't really need to know any highschool maths. Knowing calculus at a highschool level helps a lot but generally what you learnt in highschool was introduced incorrectly and will be deconstructed or made clearer.
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On March 06 2012 15:44 Sinensis wrote:
1st place for fun is discrete math. A dictionary will tell you discrete math is math that is discrete or "smooth" and not continuous... but that's very vague. It's pretty much a mix and match of different topics... all intuitive enough not to require strenuous memorization yet very fun to think about. The popular topics you learn are theoretical computing (state machines), logic, graph theory, set theory, combinatorics. topology, and some light number theory.
As someone who's working on their doctorate in computability theory, I find it interesting to see state machines listed as a popular topic, especially in front of graph theory and number theory. As far as I can tell, almost nobody knows about computability, but you're right that it's really awesome. I guess I should say that there's basically zero overlap between studying state machines as a computer scientist and studying state machines as a mathematician... In CS, you look at all the questions you might want to ask a computer to answer, say "only the ones that can be answered by an algorithm are interesting" and then explore what sorts of algorithms can answer what sorts of questions. In math, you look at all the questions you might want to ask a computer to answer, say "all the ones that can be answered by an algorithm are trivially uninteresting" and then explore the information-theoretic hierarchy/structure of the noncomputable stuff. But "noncomputability theory" doesn't have such a nice ring to it. so we use the same words that CS does. Basically, a theoretical computer scientist draws a little circle whose boundary is the halting problem, tries to fill in the interior with a detailed map of the information landscape as seen by a computer, and writes "HERE BE DRAGONS" on the infinite blank space outside the circle. A computability theorist says "fuck yo tiny circle, I'mma go meet some dragons" and zips off to explore the rest of the universe.
For the OP's question, there are already enough great suggestions on this first page of this topic; I don't feel compelled to reiterate them. I would pick up a "popular" (read: nontechnical) book about math first, and when you find something that you think is really exciting, then move to learning it in a formal, rigorous manner. You want to be doing proof-based math, because that's really the only kind of math worth learning for its own sake, but making the jump directly from "I enjoyed writing multiplication tables" to, say, diagram-chasing arguments in commutative algebra might be a bit overwhelming.
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If you want an introduction to proof-based math without taking a Real Analysis or very rigorous Linear Algebra class, I highly recommend picking up Spivak's Calculus. It's all stuff that you should have had some exposure to, so there's not a ton of new material. But working through the book and all of the examples will give you a great introduction to the basic proof methods and will get you comfortable with working with proofs, which is invaluable for any later classes that have any rigor.
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EPT
