Data Mining and Business Analytics

This course is about data mining and business analytics, the computational paradigm to find pattern and regularities in databases, perform prediction and forecasting, and generally improve their performance through the interaction with data. Business analytics allows discovering, analyzing and acting on data in business domain. It is about learning from the past to uncover trends and predict likely outcomes. Moreover, in data mining analytics it gives a framework to analyze data over time, leading to more refined outcomes and corrective actions. This course will cover the issues related to the key element of general process of Knowledge Discovery and predictive analytics that deals with extracting useful knowledge from raw data. The process includes data selection, cleaning, coding, using different statistical and machine learning techniques and visualization of the generated structures. This course will also cover the techniques and topics that are widely used in real-world data mining projects including classification, clustering, feature selection and etc. At the end of this course, students are able to understand the principles of data mining and the business analytics and obtaining hands-on experience of implementing data mining projects and therefore will greatly improve the competitiveness of students in business intelligence and analytics career as well as enhance their research skills.

This is a lecture, discussion, and project oriented class. Each lecture will focus on one of the topics, including a survey of the state-of-the-art in the area and an in-depth discussion of the topic. Each week, students are expected to complete reading assignments before class and participate actively in class discussion. Students will also form project groups (two to three people per group) and complete a research-quality class project.