Introduction to Data Analytics

Graduate

This course provides students with foundational understanding of core data analytics concepts, tools, and techniques as a basis for understanding the full range of methods available to data analytics professionals. Students are introduced to widely used methods including descriptive methods, data visualization techniques, supervised and unsupervised models for prediction and classification, times series modeling, text analysis methods, and various artificial intelligence models. Emphasis is placed on understanding the strengths of these methods, their limitations, and how they can be evaluated and used to solve practical business problems. Students are also introduced to common tools that are used to support data analytic efforts such as Excel, SAS, SPSS, Stata, R, Python, and Tableau.