Come learn about INTEGARLS like those found in the MIT Integration Bee! We'll be teaching a number of cool integration tricks, like crazy tangents and swingy-swingy.

How many primes are there? INFINITELY MANY! How many different ways can you prove that? INFINITELY MANY! Unfortunately, Splash isn’t infinitely long, so we’ll only have time to cover $$\infty - 1$$ ways.

Come learn about INTEGARLS like those found in the MIT Integration Bee! We'll be teaching a number of cool integration tricks, like crazy tangents and swingy-swingy.

Free and open source software powers the world's computer systems, from Cray supercomputers to smartphones to popular websites like Google and Facebook. Involvement in open source can provide a chance to hone one’s own software development skills, to show off technical prowess, or simply to learn from the missteps made by other developers. This class will cover a brief history of open source and provide a jumping-off point for students' own contributions to the open source software ecosystem. Students will be expected to work through simple coding exercises in-class.

Come learn about INTEGARLS from two finalists in the MIT Integration Bee! We'll be teaching a number of cool integration tricks, like crazy tangents and swingy-swingy.

How many primes are there? INFINITELY MANY! How many different ways can you prove that? INFINITELY MANY! Unfortunately, Splash isn’t infinitely long, so we’ll only have time to cover $$\infty - 1$$ ways.

HEY! Do you want to play games with MORE MATH? Take our class, and we'll play games with GRATUITOUS AMOUNTS OF MATH! In particular, we'll be studying the mathematics of game theory. In what games can we figure out which player has a winning strategy? In what games can we do this quickly? What interesting bits of math come out of such studies? You'll try to find the answers.

How many primes are there? INFINITELY MANY! How many different ways can you prove that? INFINITELY MANY! Unfortunately, Spark isn’t infinitely long, so we’ll only have time to cover $$\infty - 1$$ ways.

Come learn about INTEGARLS from two finalists in the MIT Integration Bee! We'll be teaching a number of cool integration tricks, like crazy tangents and swingy-swingy.

If you've ever worked on a program for longer than a week, you know it can start to run away from you, and become a tangled morass of code. We'll talk about how big software engineering companies like Google, Amazon, and Facebook avoid these problems and manage hundreds of thousands of lines of code without their programs degenerating into spaghetti.

Mathematical induction is one of three key methods of proof, and is a powerful tool for every mathematician. Its most basic use is in the proofs of identities such as $$0+1+2+3+\cdots+n=\frac{n(n+1)}{2}$$, but its full power extends far beyond that, into all realms of mathematics. Induction can even be used to prove that all pigs are yellow*. *Note: It is not actually true that all pigs are yellow. The proof has a hidden flaw in it. Can you figure it out? Take our class and give it a try!

How many primes are there? INFINITELY MANY! How many different ways can you prove that? INFINITELY MANY! Unfortunately, Splash isn’t infinitely long, so we’ll only have time to cover $$\infty - 1$$ ways.

Ever wondered how Google Maps finds a route so quickly, or how the Watson computer is smart enough to play Jeopardy? Well, we won’t answer those questions but we will learn about algorithms, which, sadly, have nothing to do with Al Gore.

Mathematical induction is one of three key methods of proof, and is a powerful tool for every mathematician. Its most basic use is in the proofs of identities such as $$0+1+2+3+\cdots+n=\frac{n(n+1)}{2}$$, but its full power extends far beyond that, into all realms of mathematics. Induction can even be used to prove that all pigs are yellow*. *Note: It is not actually true that all pigs are yellow. The proof has a hidden flaw in it. Can you figure it out? Take our class and give it a try!

Ever wondered how Google Maps finds a route so quickly, or how the Watson computer is smart enough to play Jeopardy? Well, we won't answer those questions but we will learn about algorithms, and we'll probably end up "creating" an algorithm along the way.

This class will teach you how to think about programming, without actually teaching you how to program in a specific language. You will probably leave this class with a better understanding of the concepts behind programming, so it should be a lot easier to pick up a language if you try after taking this class.

One word sums up probably the responsibility of any computer scientist, and that one word is "to know algorithms." We have made good algorithms in the past, and we will made good algorithms in the future. Take this class about algorithms, and the future will be better tomorrow. There is a problem: That quite frankly, computer scientists are the only profession that program our computers. We are not part of the problem; we are computer scientists. Yes, we stand by all the poor code we've written, but if we don't succeed, we run the risk of failure. As computer scientists, we are ready for any unforeseen programs that may or may not be programmed. It's time for algorithms to enter the computer science world. As many of you know, computers were very instrumental in the founding of arithmetic. Algorithms make computers efficient. What a waste it is to lose one's efficiency. Or not to have efficiency is being very wasteful. How true that is. (Verbosity leads to unclear, inarticulate things.) All you have to do is be the very best computer scientist you can be, because you're good enough, you're smart enough, and, doggone it, you can learn algorithms. (In case you're too young to remember the venerable Al Gore, you're in luck: This is not a class about Al Gore. This class is about algorithms. But if you want to learn more about Al Gore on your own time, Google his name and I'm sure you'll find my class description much more amusing!)

Mark Twain once quipped: "There are three kinds of lies: lies, damned lies, and statistics." Learn how to spot a damned lie by taking this class in basic statistics! (Side effects of this class may include the urge to write angry letters to newspapers every time they misuse or misunderstand statistics.)

We’ll approach statistics from a mathematical perspective, meaning that the results may be counter-intuitive. We’ll start off by speeding through high school statistics, and then we’ll finish by discussing some statistical “paradoxes” and how to resolve them. This class will move quickly, but if you can keep up, you should gain a much deeper understanding of the field of statistics!

You probably walk by subway route maps every day without even bothering to glance at them. Unbeknownst to you, maps like these form the basis for the rich mathematical field of graph theory. In this class, we will introduce graph theory and a few useful algorithms. It is recommended that you ride the T home from Splash - so, you know, you can do some "math on the T."

We’ll play a simple game, and all you have to do is guess the last ball! The catch is, you won’t be told the answer. You’ll have to work with your peers to collectively figure out what the last ball is going to be.

Want to think like a computer? Through several hands-on activities, we’ll discover how (basically) a computer thinks. In the process, we’ll introduce many concepts used in computer programming. You won’t learn how to program, but you will learn the core ideas common to most programming languages. Hopefully, you’ll leave with the motivation to pick up programming on your own!

How many primes are there? INFINITELY MANY! How many different ways can you prove that? INFINITELY MANY! Unfortunately, Splash isn’t infinitely long, so we’ll only have time to cover $$\infty - 1$$ ways.

How many primes are there? INFINITELY MANY! How many different ways can you prove that? INFINITELY MANY! Unfortunately, Spark isn’t ...

Tired of just learning statistics? Want to actually *do* statistics? In this class, you'll conduct a mini statistics project and ...