What parent wouldn't use anything at their disposal to help their kids succeed? We know that sitting down with our kids and helping them grasp the concepts they're learning at school is the best way to help them academically. And they probably don't need more time interacting with electronics, but Alexa offers some skills that can help students when parents aren't available. Luckily, if you have an Amazon Echo smart speaker, (in this case we recommend the Echo Dot for Kids) you have access to a wealth of brain-sharpening, knowledge-enhancing activities. To enable a skill on your Echo device, just say, "Alexa, enable [exact name of skill]."
If you enjoyed Jesse's presentation at ODSC's last Boston Big Data Conference come to ODSC East this May to hear out his colleagues. Rather than start with the statement of Bayes' Theorem, I want to use an old math teacher trick (which I realize many students hate) of trying to derive it from scratch, without stating what we're trying to derive. Rather, we'll start by modifying a problem that I described in an earlier post on probability distributions1. Bayes' gives you a way of determining the probability that a given event will occur, or that a given condition is true, given your knowledge of another related event or condition. All the examples that I've read or heard about seemed somewhat contrived and unrelated to the sorts of data analysis I was interested in.
With advances in artificial intelligence impacting every industry from healthcare to retail, it's no wonder people are scared. After all, these pesky machines can already perform a great many tasks better than us humans and it's only going to get worse. I'm not just talking about replacing mindless busywork like sorting mail and processing tax returns – I'm talking about AI systems taking on complex jobs like forecasting financial markets, diagnosing medical patients, even making optimized hiring decisions, and doing it all better than highly trained humans. Consider the field of radiology. To become a practicing radiologist in the US, an aspiring doctor must devote 4 years to undergraduate education, another 4 years to medical school and a final 4 years to a radiology residency program.
Eighty-five years ago, Harvard created a business school to train the leaders of industry and commerce. Within a decade, Harvard had institutionalized case study as its primary teaching method in the business school. Today, the case method is a fixture at most business schools. An average MBA student prepares (or is supposed to prepare) up to 600 cases during his or her two years in graduate school. The contrasts between the case method and traditional teaching methods are similar to those between case-based reasoning and rule-based systems.
In this paper, we report on the efforts at the University of Southern California to teach computer science and artificial intelligence with games because games motivate students, which we believe increases enrollment and retention and helps us to educate better computer scientists. The Department of Computer Science is now in its second year of operating its Bachelor's Program in Computer Science (Games), which provides students with all the necessary computer science knowledge and skills for working anywhere in industry or pursuing advanced degrees but also enables them to be immediately productive in the game development industry. It consists of regular computer science classes, game engineering classes, game design classes, game crossdisciplinary classes and a final game project. The Introduction to Artificial Intelligence class is a regular computer science class that is part of the curriculum. We are now converting the class to use games as a motivating topic in lectures and as the domain for projects. We describe both the new bachelor's program and some of our current efforts to teach the Introduction to Artificial Intelligence class with games.