BUAD 6721 - Big Data Analytics

Spring (2) Staff

This 2-credit elective is designed to equip students with the kinds of analytical skills used in the era of Big Data to reveal the hidden patterns in, and relationships among, data elements being created by internal transaction systems, social media and the Internet of Things. A family of non-parametric analytical methods collectively referred to as “Data Mining” methods has grown out of the Artificial Intelligence community and has become commonplace in many of the world’s leading analytics competitors. This course introduces students to one of the leading software applications for such tools (the open source system called R), and uses it to discuss several of the most frequently used techniques in Machine Learning, in both supervised and unsupervised learning. The course is taught as a combination of lectures and demonstrations on the data mining topic of the day followed by workshops wherein students work through practice problems selected to illustrate applications in various business disciplines and then complete assignments based on that material. Student teams are then required to conduct a data mining project of their own choosing.