We might think of computers as unintelligent pieces of machinery, capable of doing only exactly what we command. However, recent advances in artificial intelligence have allowed computers to perform tasks completely on their own, from working assembly lines to driving cars - even playing video games. In fact, AIs developed to play games such as Chess, Go, and Dota 2 have already surpassed even the most skilled professional players. We will briefly examine the ways in which artificial intelligence software has evolved over the past couple of decades, allowing computers to learn how to play video games even better than we can. We will analyze and implement some popular machine learning models, allowing us to create our own AI for simple video games. Finally, we will address the age-old question: are computers going to take over the world?

You use probability and statistics every day, whether you are conscious of it or not. Perhaps you look outside in the morning and think about the chance it will rain, and decide whether or not to grab an umbrella. Or maybe you think about how long it usually takes you to complete your homework, and use this as an estimate for how much time you should plan out for your next assignment. Probability and statistics are all around us in the world as well. If you have one those new-fangled iPhones with face recognition, your phone has used advanced statistical models to learn exactly what you look like and make sure it only unlocks for you. Google, among other companies, attempts to determine the probability that you will click on one of their ads, and adjusts its formulas to maximize your engagement with particular content. Despite its prevalence, probability and statistics are not always cut-and-dry. Our intuitions about these subjects don't always align with what theory dictates, and this can lead to many problems in how we interpret important findings. Thus it is our responsibility to be careful consumers of information and understand the assumptions we are making in any given situation. This course will introduce a few basic concepts of probability and statistics, as well as some more advanced. These will be used explain some truly astonishing paradoxes which arise in probability and statistics, along with some notable fallacies of statistical decision-making. The concepts will be simple at first, but we will progressively move towards more challenging (and more paradoxical!) scenarios. Be prepared to not understand every bit of the math in its entirely, but to enjoy learning about these mind-boggling situations nonetheless.

Movies are great at engrossing us in stories, building our excitement, and making us laugh or cry - but they’re not necessarily always true to reality. Sometimes this is by design (a Sharknado is obviously not an actual thing). Other times movies simply ignore things or get them wrong. Scenarios which we might take for granted in some movies – like the space battles of Star Wars – are actually physically impossible! This seminar will examine the physical realism of a few classic movie scenarios, from cars jumping draw bridges to time travel. We’ll dive into scenes from sci-fi, action, and other films. Then, drawing on concepts from kinematics, acoustics, relativity, and more (as well as just simple logic), we will discuss some scenarios which are surprisingly accurate, some which are physically impossible, and some which involve complications still being researched.

In today’s data-driven society, we put a lot of faith in statistics as a means of verification of the truth. It is used to support arguments in political debates, push products in advertisements, convey the news through catchy headlines, and provide assessment of scientific research. By its nature as a mathematical discipline, it is seen as an unbiased representation of the facts. As it turns out, this blind faith in statistics can cause a lot of problems. Statistics provides a way of distilling millions of data points down to a few numbers, so it doesn’t always capture the full picture of what’s going on in the world. At its best, this results in naïve researchers making inaccurate claims - but at its worst, bad statistics can be used by malicious parties to push misleading information. In this class, we will discuss problematic statistical fallacies through a lens which will allow us to be appropriately skeptical of statistical studies. We will see how the same sets of data can be used two convey two opposing points, how “p-hacking” can be used to push trends that do not exist, and why it is posited that the majority of published research is false. We will draw upon references to statistical pop culture, analysis of simulated data sets, and student input to address real-world concerns and become careful consumers of information.

We use computers every day, but most of us do not have any idea of how they actually work. Most people probably think they are too complicated to even try to understand. In reality, two fairly simple concepts account for 99 percent of what computers do! We will cover these two concepts - binary numbers and logic operations - and explain the ways in which they are implemented in computers to store and manipulate information.

As computers play an ever-increasing role in our day-to-day lives, coding is becoming a more and more valuable skill to have. Coding has a very wide variety of applications in many different fields, and it's actually not as difficult to pick up as most people would think. This class will introduce you to the easy and popular programming language of Python. We'll get you up to speed and writing programs as soon as possible, without worrying too much about the nitty gritty.