BAN 7700 Machine Learning

This course is designed to provide a broad overview of machine learning concepts and applications aimed at automating and advancing analytics performance. The course distinguishes itself by anchoring it’s content on big data phenomena and thus domain knowledge, technology and math are integrated throughout the course. The course covers five broad segments of topics in machine learning driven analytics: Fundamentals (Algebra, Matrices & probability for ML), algorithms (& Optimization techniques), supervised learning, unsupervised learning and managerial application (thought leadership & usage) of ML in big-data analytics. This course provides a unique balance between theory and application along with data driven cases - thus it aims to impart expert skills along with encouraging thought leadership. An integral part of machine learning analytics is the use of IT tools to support the organization and analysis of data - hence the students will learn to apply various machine learning analytics tools including R.  Prerequisite(s): BAN 7010
Credits: 3.0