This course introduces the history, concepts and practices of extracting information from large databases to support business decisions using descriptive, prediction, and prescriptive analytics, The course covers various analytical techniques to turn data into information beginning with data preparation and exploration and then using a number of well-defined data mining tasks such as classification, regression, and clustering. Prerequisites: Lower-level core.
This course introduces best practices of data analytics to create a more competitive and profitable organization. Students will learn how Big Data interacts with business, and how to apply data analytic methodologies to create value for an organization. The course includes hands-on applications of sophisticated data-analysis functions and methodologies to real world data sets with cutting edge software and tools. The course also includes business cases of how the leading digital companies embrace big data culture and the use of data analytic techniques to out-compete rivals in their industry and to be more profitable than traditional companies in the global business environments. This course is a capstone course for the Global Business-Data Analytics concentration. Prerequisites: Lower-level core.
This course is an advanced course in data mining. Data mining concepts are extended from Business Data Mining I to include additional models and advanced applications of the models previously introduced, such as sentiment analysis and neural networks. Emphasis is placed on working with larger data sets and the entire cycle of a data analytics project. Prerequisites: DA 4410.