In this course, we will learn how to use modern tools for analyzing and extracting information from real-world datasets to answer statistical inference questions. Potential datasets may include medical, social network, and weather forecasting data. For each dataset, we will explore tailored methods for processing, analyzing and visualizing the results such as regression, principal component analysis and clustering. With the increasing trend of big data, we will also focus on the computational aspects of working with large-scale datasets and present scalable approaches for addressing these challenges. We ask students to bring a laptop if possible to implement the methods during the course.