53:716:502
Business Analytics (3)
Managers, regardless of their functional responsibilities, make decisions that are driven by data and analysis. This course will help in development of important skills in data analysis and modeling. Through rigorous and guided exercises, students will gain the ability to synthesize pieces of analyzed information to make better decisions. A combination of theoretical and practical mathematical and software tools will be used. In addition to regular lectures, the course will employ computer exercises, case analysis, discussions, and team presentations. Special emphasis will be on making the results/decisions end-user-friendly.
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53:716:504
Management Science (3)
This course introduces students to the application of quantitative models and their related mathematical techniques, to solve real-world business problems. A blend of analysis and synthesis is emphasized to generate meaningful solutions for managers. Topics include single- and multiple-criteria decision methods, project scheduling, transportation and assignment problems, queuing theory, and decision analysis.
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53:716:513
Operations Management Productivity and Quality (3)
This course provides the foundation for managing the operations of both manufacturing and service organizations. Topics include operations strategy, product and service design, inventory management, facility and capacity planning, forecasting, quality management, supply chain management, and just-in-time operations.
Prerequisite: 53:135:502.
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53:716:516
Total Quality Management (3)
This course provides the development, practice, and processes of quality management. It focuses on increasing productivity through continuous improvements in quality. Case studies and role-playing exercises are used in the instruction.
Prerequisite: 53:716:513.
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53:716:519
Service Operations Management (3)
Service industries account for almost 80 percent of the workforce in the United States and also the majority of the workforce in other industrialized economies in the world. This course provides a state-of-the-art overview of service operations management. In addition, it will help students structure and solve problems commonly found in service industries using analytical models, as well as develop an awareness of the opportunities of information technology in enhancing a service firm's competitiveness. Topics include service design, service quality, queuing analysis, capacity management, and technology in services.
Prerequisite: 53:716:513.
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53:716:521,522
Directed Study in Operations Management (3,3)
Supervised by an individual faculty member and approved by the associate dean of graduate studies.
Prerequisite: 53:716:513.
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53:716:523
Global Operations Management (3)
This course utilizes recent innovations of cutting-edge technology to address issues of managing global operations. Text and cases draw on the experience of pioneers in global operations. The use of restructuring and reengineering to increase speed, reduce costs, and enhance innovations will be thoroughly discussed.
Prerequisite: 53:716:513. This course may also count toward an international business concentration.
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53:716:531
Supply Chain Management (3)
This course provides the understanding of how supply chain design and planning decisions impact the performance of the firm as well as the entire supply chain. It links supply chain structures and logistical capabilities in a firm and utilizes the concepts learned in various functional areas such as management, marketing, and finance within the context of supply chain management. A blend of lectures and case studies are employed to facilitate learning of course materials.
Prerequisite: 53:716:513.
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53:716:535
Big Data Analytics and Visualization (3)
This course provides students with an in-depth introduction to the Hadoop ecosystem, which is an environment used by companies to store and manipulate Big Data of a size and scale that cannot be handled by traditional databases. The course also provides exposure to state-of-the-art data mining algorithms for clustering, classification, and collaborative filtering (a technique used by businesses to recommend products to customers). Students will also learn information design, specifically tactics for visualizing Big Data.
Prerequisites: 53:716:502 and 53:623:517.
Note: Students should have familiarity with the Python programming language before coming into this course.
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53:716:540
Social Media and Sentiment Analysis (3)
This course enables students to ingest Big Data from APIs for social media platforms such as Twitter. After assembling data from social media, students learn to analyze the data to gain business insights. Concepts for the analysis of social media, such as community detection and assignment, node centrality, information diffusion, and opinion formation will be presented. Students will also learn the process for sentiment extraction, opinion mining, and recognizing opinion spam.
Prerequisites: 53:716:502 and 53:623:517.
Note: Students should have familiarity with the Python programming language before coming into this course.
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53:716:670
Special Topics in Operations Management (3)
Topics vary from semester to semester. Consult the associate dean of graduate studies for specific content each semester. Students may enroll in more than one special topics course.
Prerequisite: 53:716:513.
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