DA 350 - Advanced Methods for Data Analytics
This course is designed to develop students' understanding of the cutting edge methods and algorithms of data analytics and how they can be used to answer questions about real-world problems. These methods, and the underlying models, can be used to learn from existing data to make predictions about new data. The course will examine both supervised and unsupervised methods and will include topics such as clustering, classification, and network analysis.
Class will typically consist of introductions and hands-on computing exercises. The course will be taught using R, RStudio, and RMarkdown, but the concepts learned will frequently apply across multiple programming languages and data management systems. You are going to learn the most popular machine learning algorithms in data analytics.