PG COURSES OFFERED IN SPRING 2020-2021 (OPERATIONS MANAGEMENT)

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.

[Previous Course Code(s): ISOM 582, ISMT 582] Properties of a random sample, sufficient statistics. Point and interval estimation, hypothesis testing, optimality of estimators and tests, linear regression and analysis of variance.

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.

[Previous Course Code(s): ISOM 561, ISMT 561] Introduction to management of business processes that produce goods or services: topics include operations strategy, process analysis, queuing systems, inventory management, quality management, process improvement and other important issues.

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 focuses on the products and processes in the financial industries. It analyzes and evaluates the designs and performances of the internal operations and the different distribution channels of the financial institutions, and identifies opportunities for continuous improvement in productivity and efficiency. It also covers the issues of quality control and operational risk management, the application of IT in the industry. It will also discuss the automation/outsourcing of the financial operations for non-financial institutions to improve the financial performance and risk management in the supply chain.

[Previous Course Code(s): ISOM 6790H] This course requires students to attend at least four industry workshops and one company visit. It aims to increase students' exposure to the operations management practices in different industries and enhance their communication skills. No assignment and exam will be needed. Graded P or F.

[Previous Course Code(s): ISOM 580, ISOM 669B, MGMT 650F] This course is open to all MBA students who need to utilize spreadsheets to create and analyze business models for decision making and/or managerial insights. Practical exercises and case studies are used to illustrate the concepts and practices of business modeling and to build competency in using spreadsheets for advanced applications. Graded P or F.

[Previous Course Code(s): ISOM 571, ISMT571 ISMT669I] The science and technology of informed decision making with focus on optimizing business processes. Spreadsheet decision modeling in Excel used throughout. Emphasis on problem formulation, spreadsheet-based solution methods, and managerial insights. Applications to managerial decision problems in diverse industries and functional areas including finance and accounting, human resource, marketing, and operations.

Operations Management (OM) deals with the production and delivery of goods and services. Eight applications in OM will be covered in this course. The principal purpose is to expose students to a wide range of good case histories in order to enhance their repertoire and experience in OM.

This special topic course focuses on modern techniques for predictive analytics. Different statistical techniques such as analyzing time series data and its financial applications, text data analysis and causal analysis will be discussed. Practical cases will also be introduced into the course.

Understanding and knowing individuals’ behavior and feedback through data is getting popular in providing suggestions on business strategies and indicating ways for enhancement of services as well as facilitating improvement. This course introduces statistical modeling methods for behavioral data. Both theory and practice by using statistical programming tools will be discussed in the course.

This course focuses on how to prepossess and visualize real business data using Python, identify and predict the statistical patterns of data, and explore the real-world application with statistical insights. Both theoretical concepts and methods will be discussed, as well as the details of the implementation with Python.

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

This course offers a unique opportunity for the students to participate in real business projects and to apply what they have learned in other courses in solving business problems. Student teams will work under faculty supervision to solve global operations management related problems and identify improvement opportunities for both service and manufacturing businesses. They will also gain practical experience in planning and executing a real business project.