Courses

AI isn't as complicated as it might seem. By referencing everyday applications such as targeted marketing, web analysis, disease diagnosis, weather forecasting, and fraud detection, we can build upon pre-existing mental models to understand the underlying mechanics of AI. This course will present a high-level overview of three main topics in AI: introductory machine learning concepts, basic analysis and visualization of data, and basic programming in R (a programming language commonly used in data science and well suited for those with little to no programming experience). The course will include lectures and hands-on, interactive problem-solving exercises to help students connect conceptual challenges to tangible data solutions. Examples will be based on real-world problems in weather, marketing, biology, stocks, neuroscience, medicine, and generative AI. By the end of the course, students will be able to apply basic AI techniques to practical applications to draw meaningful conclusions.