An Introduction to Data Science
Living in the information age, we find ourselves surrounded and overwhelmed by data, making it imperative for us to find ways to identify the data we need, classify and organize it, and draw conclusions from it. Data science is a very practical discipline with many applications in business, science, and government, such as targeted marketing, web analysis, disease diagnosis and outcome prediction, weather forecasting, credit risk and loan approval, customer relationship modeling, and fraud detection. This course presents a high-level overview of three main topics: basic analysis and visualization of data, introductory machine learning concepts, and basic programming in R (a programming language that is widely used for data analysis). The course will include lectures and hands-on, interactive problem-solving. Examples will come from real-world problems in weather, marketing, biology, stocks, neuroscience, medicine, and other disciplines. By the end of the course, students will be able to apply data science techniques to real-world applications in order to draw meaningful conclusions.