This course extends and deepens the material you learned in business analytics. We will apply these methods in more unstructured and diverse situations, introduce new analytics tools and methods (including Tableau Visualization, text mining, and random forests), and study a modern framework for overfitting reduction called regularization that underlies much of modern machine learning. This course does not require coding or knowledge beyond Business Analytics, but the mathematical sophistication level will be somewhat more advanced.
- Attendance at the first class is compulsory
- Completion of pre-class work is compulsory in order to remain in the class
- There will be a final exam
Senior Lecturer in the Discipline of Decision, Risk and Operations; Director Center for Pricing and Revenue Management and Business Analytics Initiative
Daniel Guetta is Senior Lecturer in Discipline at the Columbia Business School, and the Director of the Business Analytics Initiative at the Columbia Business School and Columbia Engineering. His research focuses on the ways companies can harness the power of data and analytics to drive value. He teaches classes in business analytics, including data science, pricing, supply chain management, and technical tools such as...