Three credits. Prerequisite: open only to graduate business students, others with consent. Not open for credit to students who have passed BADM 5181.
Covers some of the more familiar classical inference procedures and the basic statistical concepts that are often essential to the interpretation of business data. Methods of understanding variability, and detecting changes are explored using descriptive, exploratory, and inferential statistics found in widely available statistical packages. Topics include: iscrete and continuous random variables, sampling, confidence intervals, hypothesis testing, and linear regression.
An operations manager is concerned with designing, operating and controlling a system for producing goods and services. Design decisions include selecting a process technology, organizing jobs, selecting vendors, and developing the location and layout of facilities. Operating the system involves planning and scheduling work and material flow, controlling quality, and managing inventories. General systems concepts and models are developed and applied. Topics include process flow analysis, inventory systems, waiting line analysis, quality design, capacity resource planning, project management, and integrating operations with the firm’s strategic plans.
Three credits. Prerequisite: open only to MBA and MSBAPM students, others with consent. Not open for credit to students who have passed OPIM 5182.
Emphasis on business applications and how to structure the development and use of information systems for maximum benefit to the organization. Topics include: decision support systems, impact of the computer upon individual and organizations, competitive implications, technology change, telecommunications, and control of information systems resources.
Variable (1-5) credits. Prerequisite or corequisite: BADM 5180.
Introduction to key issues and concepts in data analytics. Begins by delineating the differences between standard statistical analysis, including model estimation and evaluation, and the data driven approach of data analytics. A good deal of emphasis is placed on critical issues underlying almost all data analytics projects, including data quality (accuracy, objectivity, and reliability), missing values, outliers, and data standardization. Introduction to basic analytics techniques and processes.
Variable (1-5) credits. Prerequisite: open only to MBA students, others with consent. Not open to students who have passed BLAW 5182.
Information technology (IT) has had a dramatic impact on how individuals and organizations work, and is an important force shaping entire industries and value creation by firms. Most business school graduates will have IT related responsibilities during their careers, no matter which functional area they are in, and will be involved in efforts to select, adopt, and exploit information technologies in support of business goals. The goal of this course is to prepare students to execute these responsibilities effectively, and to be able to do so even as the set of available technologies changes over time. The course presents students with frameworks that let them analyze business situations involving IT in a structured way. It will also help them develop sophisticated understanding of the links between IT, business strategy, and business process. They will also gain an appreciation of the organizational and management practices that complement IT investments.
Variable (1-5) credits. Corequisite: BADM 5181; open only to students in the full-time MBA program.
Overview and introduction to operations management. Focus on the process view of operations and develops a framework for process analysis and improvement with and without variability.
Variable (1-5) credits. Prerequisite: OPIM 5183.
Built on the previous module, covers critical and specific topics in operations management, including inventory, quality, lean operations, and operations across firms (supply chains). It introduces both qualitative strategies and quantitative models concerning these topics.
Examines the project management process and the management of a portfolio of projects, with focus on techniques to overcome the pitfalls and obstacles that frequently occur during a typical project. Designed for business leaders responsible for implementing projects, as well as beginning and intermediate project managers.
Introduction to market-leading techniques that help to identify and manage key data from business processes. Provides the essential tools required for data mining and business process re-engineering. Combines lecture, class discussion and hands-on computer work in a business-oriented environment.
Three credits. International students must have completed both a spring term and a fall term prior to taking this course. Instructor consent required. Students taking this course will be assigned a final grade of S (satisfactory) or U (unsatisfactory).
Gives students real-world experiences in applications of analytics and/or project management through an internship or industry project undertaken individually with a company under the joint supervision of a faculty member and the student’s field supervisor. Student performance will be evaluated on the basis of an appraisal by the field supervisor and a detailed written report submitted by the student.
Three credits. Prerequisite: OPIM 5604.
Explores techniques and best practices in visualizing data. From simple cross tabs to more complex multi-dimensional analysis, explores why particular data visualizations can better illustrate patterns and correlations inherent in the data itself. Examines cognitive function and its role in data visualization designs; showing that data visualization can reveal answers and questions alike. Utilizing state of the art software, the use of parameters, filters, calculated variables, color, space and motion to visually articulate the data are surveyed. The use of dashboards to quickly reveal data-driven information that has daily relevance to executives, managers, supervisors and line personnel are investigated. Common pitfalls in visualization design and why less is often more are considered.
In-depth, hands-on exploration of various cutting-edge information technologies used for big data analytics. The first half focuses on using big data management techniques for ETL (extract-transform-load) operations. The second half focuses on using big data analytics tools for data mining algorithms including classification, clustering, and collaborative filtering. Extremely hands-on, requiring students to spend significant time working with large datasets. Students are expected to have taken at least one course in data modeling and one course in data mining (please see pre-requisites) or have significant related work experience. Students should expect to become familiar with the Unix operating system, as well as with programming in Python. Students may be required to install some software on your computers on your own, with very little support, if any, from the instructor or anyone else. Students should be willing to troubleshoot any issues during installation, drawing help from Google searches.
Three credits. Prerequisite: OPIM 5604.
Helps students develop proficiency in data analytics using R for statistical inference, regression, predictive analytics, data mining, and Text mining: analyzing twitter and social network data. Combines lectures, hands-on exercises, business case discussions, and student presentations in a professional environment.
The use of techniques from statistics and optimization to implement ABI systems. Introduction to the fundamentals of decision support systems, genetic algorithms, ABI systems, and their applications to diverse management contexts. Students will learn how to use tools such as Excel VBA, Evolutionary Solver, and RExcel (R language for statistical analysis) to develop ABI applications.
Exposes students to a wide array of real consulting situations in business analytics operations and financial services, and will teach students methods of addressing these problems using spreadsheets, simulation, and optimization methods. While consulting encompasses many specific tasks and requires broad functional knowledge, there is an increased need and appreciation of the usefulness of analytical consulting.
Three credits. Prerequisite: OPIM 5270.
Application of project management knowledge, tools, and techniques to the planning, organization, and delivery of international development projects and programs. Funded by institutions (e.g., multilateral or regional development banks, United Nations associated agencies, bilateral government agencies, non-governmental organizations, global funds), these projects/programs cover a wide range of sectors and focus on poverty reduction/alleviation and improving living standards of people in developing and emerging countries, assistance to victims of natural or people caused disasters, capacity building and development of basic physical and social infrastructures, and on promoting environmentally sound development and basic human rights protection.
Uses case studies to illustrate the variety of projects and the issues involved in managing them from resource concerns to the criticality for demand estimation; from conflicting objectives of stakeholders to social responsibility issues; from knowing the customer to project finance challenges. These cases inductively teach advanced topics in the management of large projects, such as planning and scheduling issues, costing and budgeting, staffing and organizing, project finance structuring, sustainability and environmental issues, and the challenges in planning and execution of these complex projects. Agile project management methodologies for effectively and efficiently undertaking knowledge-based projects of today. Practical guidance and experience around the process of initiating, delivering, and evaluating analytics projects.
Reviews the foundational knowledge necessary for MSBAPM student to be a well-equipped analytics professional. Communication skills are essential to convey technical analytical content. Topics such as Public Speaking, Emotional Intelligence, Non-Verbal Communication, Requirements Gathering, and Etiquette via multiple modes of Communications (email, phone, in person, one to one, and one to group) and more will be discussed and practiced. Such skills are critical to professional success as the industry is changing to require technical depth and also the ability to connect it to the business. Topics covered include: Communication Skills – Bridging the Gap between the Technical and Business; Presentations Skills – Technical Content to the Business; Networking with Analytics Professionals
Three credits. Prerequisite: open only to MBA students, others with consent. Not open to students who have passed BLAW 5182.
Review of algebra followed by introduction to functions, limits, differentiation, integration, vectors, matrices and linear programming. Examples and applications of mathematical topics to business problems.
Three credits. Prerequisite: open only to Business Analytics and Project Management M.S. students, others with consent.
Advanced level exploration of statistical techniques for data analysis. Students study the concepts of population and sample; iscuss the difference between population parameters and sample statistics, and how to draw an inference from known sample statistics to usually unknown population parameters. Topics will focus on rigorous statistical estimation and testing. Prepares students with the skills needed to work with data using analytics software.
Introduces the techniques of predictive modeling in a data-rich business environment. Covers the process of formulating business objectives, data selection, preparation, and partition to successfully design, build, evaluate and implement predictive models for a variety of practical business applications. Predictive models such as neural networks, decision trees, Bayesian classification, and others will be studied. The course emphasizes the relationship of each step to a company’s specific business needs, goals and objectives. The focus on the business goal highlights how the process is both powerful and practical.
Examines the management control problems and systems development processes from the dual perspective of (a) managers of the computer information system, and (b) the organization as a whole, including persons who interact extensively with the systems personnel or are administratively in a position to influence the information system.
Discusses business modeling and decision analysis. Covers topics such as optimization, simulation, and sensitivity analysis to model and solve complex business problems. As spreadsheets are often used as software tools for such problem solving, the course will emphasize developing high quality spreadsheets to ensure that the objectives of the model are clear, defining the calculations, good design practices, testing and presenting the results.
Three credits. Prerequisite: OPIM 5270; open only to MBA and MSBAPM students, others with consent.
Introduces the art and science of project risk as well as continuity management and cost management. Risk management ensures a project is completed through both general and severe business disruptions on local, national and international levels. Managing the risk of a project as it relates to a three-part systematic process of identifying, analyzing, and responding is examined through actual case studies. In addition, this course will examine the process of cost management, early cost estimation, detailed cost estimation, cost control using the earned value method, issues related to project procurement management, and the different types of contracts for various scope scenarios.
Three credits. Prerequisite: OPIM 5604; open only to MBA and MSBAPM students, others with consent.
Discusses data mining techniques that can be utilized to effectively sift through large volumes of operational data and extract actionable information and knowledge (meaningful patterns, trends, and anomalies) to help optimize businesses and significantly improve bottom lines. The course is practically oriented with a focus of applying various data analytical techniques in various business domains such as customer profiling and segmentation, database marketing, credit rating, fraud detection, click-stream Web mining, and component failure predictions.
Capstone course involving a live data analytics project, where students will need to integrate their knowledge of data analytics and project management. Using the skill sets of predictive modeling, data management, process models, and data mining techniques, students will investigate a real problem through data analytics, and will use their project management skills to complete the project within time and budget constraints.
Three credits. Prerequisite: open only to MSBAPM and MBA students, others with consent.
Discusses the business risks arising from digital information processing and identifies ways to prevent, detect, and mitigate negative consequences of information security breaches. First, students will be introduced to the basic principles of information security, its role in reducing information risk exposure, and tools and solutions that can be used to prevent information loss or costly business interruptions. Second, students will explore the role of information technology governance in business organizations, discuss important relevant laws (for example, Sarbanes-Oxley Act of 2002), reporting requirements, and industry standards for IT Governance (for example, COBIT). Third, students will study the process of information systems audit, IT audit tools, and audit procedures to help in detection and prevention of fraud.
Variable (1-6) credits. May be repeated for credit.
Introduces many of the most exciting concepts emerging in the field of consumer oriented Internet working, including high-speed access [cable modem, satellites and digital subscriber lines (DSL)]
and infrastructure developments such as gigabyte networking with asynchronous transfer mode (ATM). Evaluates the emerging directions in EC that are expected to shape both consumer and business applications in the coming decade. A “macro perspective” is used to examine the technical and managerial aspects of electronic commerce. Focus is on questions such as: What are or will be the key attributes of current and future digital products, payment systems, online retailing, and banking? How are these systems designed and implemented? What are the different mercantile processes and tradeoffs associated with these processes? What impact has global connectivity made on traditional supply-chain(s)?
Variable (1-3) credits. Instructor consent required. May be repeated for a total of 12 credits.
Faculty-student interaction on a one-to-one basis involving independent study of specific areas of operations management, operations research and/or information management. Emphasis, selected by the student, may be on theoretical or applied aspects. A written report is required.
Variable (1-6) credits. Prerequisite: open only to doctoral students; instructor consent required. May be repeated for a total of nine credits. Students taking this course will be assigned a final grade of S (satisfactory) or U (unsatisfactory).
In-depth investigation in special topics in Operations and Information Management.
Three credits. May be repeated for a total of 12 credits.
Several advanced analytical methods that are relevant to students’ areas of research will be studied in depth in this seminar. Topics may include special mathematical programming; complex decision making; linear models; advanced statistical analysis; and stochastic processes.
Three credits. May be repeated for a total of 12 credits.
Introduces doctoral students to the current research concerns in the field of Operations Management. Acquaint students with the variety of research tools used in the field, enabling them to critically evaluate the research of other scholars in the field as well as to develop research skills in identifying potential research problems to be analyzed.
Three credits. May be repeated for a total of 12 credits.
A topic on a significant applied or theoretical aspect of information systems will be chosen. Broadly, these aspects will encompass modeling, design, implementation, testing, and operation of computer information systems, and the implications of information technologies for the organization.