Covers various discrete and continuous probability models and their applications in business problems, estimation and testing of hypotheses, simple and multiple linear regression analysis.

This course describes the multiple regression method and its variants as exploratory and predictive models for fact-based management and data-driven decision making. The course adopts a case-based approach.

This course focuses on various visualization analysis tools for business decisions. Making good use of visual analytics helps summarize and analyze large amounts of data effectively. In this course, the topics like visualization framework, visual analytics for spatial, temporal, network and textual data, and dynamic visualization will be included. Reporting visualization results for business decisions will also be discussed.

The course presents  concepts of social media and networks, methods and techniques  to explore and analyze the data crawled from social media and network, and business application of data mining of social network. . All these will be discussed in the context of finance and marketing. Python is the unique programming language for all cases and projects.  

This course presents classical and modern approaches for analyzing multivariate and high dimensional data, including principal components, factor analysis, discriminant analysis, clustering, new developments in dimension reduction, large-scale covariance matrix estimation and multiple testing. All of these approaches will be covered in the context of Marketing, Finance and other important business areas. Computational issues for both traditional and new methodologies will also be discussed.

The science and technology of informed decision making with a focus on optimizing business processes. Spreadsheet decision modeling in Excel is used throughout. Emphasis is on problem formulation, spreadsheet-based solution methods, and managerial insights. Applications relate to managerial decision problems in diverse industries and functional areas including finance and accounting, human resources, marketing, and operations.

This course provides an overview of information privacy and management in the information economy. It covers the fundamental concepts and dimensions of privacy; the impact of Internet marketing, customer relationship management, Web personalization, and data mining on consumer privacy; privacy enhancing technologies; and regulation of business practices.

Data plays an increasingly important role in business decision making. This course introduces the key concepts and applications of business analytics in the world of Big Data. Example business problems to be solved analytically include customer relationship management, financial trading, social media marketing, search engine strategy, etc. Hands-on experience with popular data analytical tools will be included.

This course helps students develop better analytical skills in approaching strategic and tactical business decisions. Students will learn to derive solutions or conclusions that require critical thinking, quantitative analysis, and strategic reasoning skills. These skills are essential and indispensable for major business decisions.

This course covers selected topics in business analytics. Topics vary with recent interest, market emphasis and latest advancements.

This course provides students practical experience in business analytics through independent study and business case analysis under the supervision of faculty members. 

This course introduces the emerging technological paradigm for managing "big data”. Topics covered include a range of big data technologies, such as HDFS, MapReduce, Spark, Hive, Pig, etc.

This course focuses on the critical issues in the design, production and delivery of tangible goods, as well as intangible goods, in the business world. Topics include process analysis, capacity and bottleneck issues, waiting time management, inventory management, quality management, lean systems, supply chain management and e-commerce. Quantitative and qualitative tools will be taught to analyze the problems and create innovative solutions.

This course introduces students to business application modeling using Visual Basic Applications (VBA) in Excel. Students will learn to develop applications in different business areas, including finance, marketing, technology operations, etc. Essential features of VBA needed for application development will be introduced as part of the course and hence no prior experience with VBA is needed. Emphasis is on extensive hands-on problem solving.

This course offers essential knowledge and tools for managers of digital business. Topics include e-commerce models, web analytics, Internet marketing, Internet pricing and strategy, web-based personalization, online-intermediaries, etc.

This course is about how to preprocess real business data using Python (mainly using pandas), identify and predict the patterns of data and finally explore the real-world application of these patterns.