In this course, you will cover key unsupervised learning techniques including association rules, principal components analysis, and clustering. You will also review integration of supervised and unsupervised learning techniques. Participants will apply data mining algorithms to real data, and will interpret the results. A final project will integrate an unsupervised task with supervised methods covered in predictive Analytics 1 and 2. Students will use R, a free software environment with statistical computing and graphics capabilities. Note: If you prefer to work in Excel or Python, this course is offered using Solver (an Excel add-in) or Python.
Dr. Inbal Yahav
Dr. Inbal Yahav is a faculty member at the Graduate School of Business Administration, Bar-Ilan University, Israel. Her research interests lie in the areas of statistical modeling and social media, with a focus on users' behavior in social networks, interactions and dynamics among users, and statistical modeling of heterogeneous behaviors. Dr. Yahav's research to-date focuses on two domains. The first domain is cyber security and privacy, and in specific privacy unawareness and unintentional information leakage in social networks. The second domain is statistical modeling of sub-populations in big data. Dr. Yahav has presented her work at multiple Information Systems conferences and has published papers in books and journals.