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  Rutgers Business School: Graduate Programs-Newark and New Brunswick 2018-2020 Course List and Descriptions Management Science and Information Systems  

Management Science and Information Systems
22:135:571 Calculus for Managers (2) Topics include functions, lines, quadratic equations, exponential and logarithmic functions, limits, derivatives, partial derivatives, one and two variable function optimization, Lagrange multipliers, matrix algebra, and solutions to linear equations.
22:135:572 Statistics for Managers (2) Topics include descriptive statistics, elementary probability, discrete distributions, normal distributions, sampling distributions, small and large sample inference for an unknown population mean, and proportions.
22:198:504 Information Technology for Managers - FT (2) The objective of this course is to study management's role in the development and use of information systems that help businesses achieve their goals and objectives. Information technology (IT) has been the driving force behind the new way of doing business. IT has enabled modern organizations to make tremendous strides in productivity, has opened new markets, and has created new product and service opportunities. Managers should understand how IT could help to organize the complexity of modern organizations; manage relationships with customers, suppliers, and employees; and improve work efficiency.
22:198:603 Business Data Management (3) The purpose of this course is to provide students with an understanding of database technology and its application in managing data resources. The conceptual, logical, and physical design of databases will be analyzed. A database management system such as ORACLE or INGRES will be used as a vehicle for illustrating some of the concepts discussed in the course. Prerequisite: Background in a procedurally oriented language (C preferred) or permission of the instructor.            
22:198:604 Computers and Information Systems (3) This general concepts course provides an understanding of the hardware, software, and other components of computer systems; it surveys file and database management systems and telecommunications and networks; analysis, design, and development of computer-based information systems; and evaluation of computer acquisitions. This course is an alternative to 22:198:605 Introduction to Software Development.
22:198:605 Introduction to Software Development (3) Fundamentals of the C/C++ programming language comprise a major part of this course.  Introduces students to procedural and object-oriented programming. Topics from data storage, systems analysis, and database systems are also covered.
22:198:609 Information Technology for Managers - PT (2) The objective of this course is to study management's role in the development and use of information systems that help businesses achieve their goals and objectives. Information technology (IT) has been the driving force behind the new way of doing business. IT has enabled modern organizations to make tremendous strides in productivity, has opened new markets, and has created new product and service opportunities. Managers should understand how IT could help to organize the complexity of modern organizations; manage relationships with customers, suppliers, and employees; and improve work efficiency.
22:198:611 Security for Electronic Commerce (3) The objective of this course is to introduce to students the emerging area of electronic commerce (EC) and the security challenges and threats in EC, and provide them with an understanding of the state-of-the-art EC security technologies. In particular, this course discusses security requirements for electronic commerce such as identification and authentication, authorization and access control, data integrity, confidentiality, nonrepudiation, trust, and regulation. Discusses various security standards including network security architecture standards, data encryption standards, data integrity standards, digital signature standards, authentication standards, certification standards, electronic data interchange standards, and electronic mail standards. It also discusses the emerging internet standards, firewalls, public key cryptography standards, Java security, Lotus Notes security, database security, security payments such as SET (secure electronic transaction), digital cash and digital checks, and smart card technology.
22:960:575 Data Analysis and Decision-Making (3) Introduces statistics as applied to managerial problems. Emphasis is on conceptual understanding as well as conducting statistical analyses. Students learn the limitations and potential of statistics, gain hands-on experience using Excel, as well as comprehensive packages, such as SPSSŪ. Topics include descriptive statistics, continuous distributions, confidence intervals for means and proportions, and regression. Application areas include finance, operations, and marketing. Introduces the basic concepts of model building and its role in rational decision-making. Knowledge of specific modeling techniques, such as linear and nonlinear programming, decision analysis, and simulation, along with some insight into their practical application is acquired. Students are encouraged to take an analytic view of decision-making by formalizing trade-offs, specifying constraints, providing for uncertainty, and performing sensitivity analyses. Students form groups to collect and analyze data, and to write and present a final report. Prerequisite: 22:135:572 with grade of B or better.        
26:198:621 Electronic Commerce (3) This course will cover the theoretical foundations, implementation problems, and research issues of the emerging area of electronic commerce. It will discuss technological, conceptual, and methodological aspects of electronic commerce. The list of topics to be covered  includes: fundamentals of internet technology, pricing of and accounting for internet transport, security problems of the internet, electronic payment systems, online financial reporting and auditing, intelligent agents, web measurements, electronic markets, and value chain over the internet. The coursework will include presentations of research articles, in-class discussions, and a final course project researching one of the problems of electronic commerce.
Prerequisites: Basic computer literacy; introductory courses in computer information systems and economics.
26:198:622 Machine Learning (3) Basic theory of rule-based systems and Bayes networks. Alternative architectures for managing uncertainty. Use of probabilistic logic to model causality. Related ideas from machine learning, neural networks, and genetic algorithms. Applications to auditing, marketing, and production.
26:198:641 Advanced Database Systems (3) Emphasizes the functions of database administrator. Includes survey of physical and logical organization of data and their methods of accessing, and the characteristics of different models of generalized database management systems. Prerequisite: A master's-level course in databases such as 22:198:603 or NJIT CIS 631.          
26:198:642 Multimedia Information Systems (3) This course covers principal topics related to multimedia information systems. These include organizing multimedia content, physical storage and retrieval of multimedia data, content-based search and retrieval, creating and delivering networked and multimedia presentations, and current research directions in this area. Prerequisite: A master's-level course in databases such as 22:198:603 or NJIT CIS 631.        
26:711:561 Mathematical Methods for Economics (3) Explores the quantitative tools and principles used to model operational procedures in economic and business systems: types of variables, mathematical sets, and functional forms in constrained and unconstrained optimization. Other topics include tractability, duality, Kuhn-Tucker theory, algorithms, and computation. Prerequisite: Differential calculus.
26:711:651 Linear Programming (3) A survey of linear programming and its applications. Topics include linear programming models, basic simplex method, duality theory and complementary slackness, sensitivity analysis, degeneracy, matrix notation and revised simplex method, special linear programs such as transportation and network flow theory, applications in statistics, economics and finance models of linear programming, game theory, and introduction to interior point methods. Prerequisite: Undergraduate linear algebra.
26:711:652 Nonlinear Programming (3) Fundamentals of nonlinear optimization, with an emphasis on convex problems. Gradient, Newton, and other methods for unconstrained problems. Projection, linearization, penalty, barrier, and augmented Lagrangian methods for constrained problems. Lagrangian functions and duality theory. Assignments include computer programming and mathematical proofs. Prerequisite: 26:711:651.
26:960:575 Introduction to Probability (3) Foundations of probability. Discrete and continuous simple and multivariate probability distributions; random walks; generating functions; linear functions of random variable; approximate means and variances; exact methods of finding moments; limit theorems; stochastic processes including immigration-emigration, simple queuing, renewal theory, and Markov chains. Prerequisite: Undergraduate or master's-level course in statistics.        
26:960:577 Introduction to Statistical Linear Models (3) Linear models and their application to empirical data. The general linear model; ordinary-least-squares estimation; diagnostics, including departures from underlying assumptions, detection of outliners, effects of influential observations, and leverage; analysis of variance, including one-way layouts, two-way, and higher dimensional layouts, partitioning sums of squares, and incomplete layouts (Latin squares, incomplete blocks, and nested or repeated measures). Emphasizes computational aspects and use of standard computer packages such as SAS. Prerequisite: Undergraduate or master's-level course in statistics.      
26:960:580 Stochastic Processes (3) Review of probability theory with emphasis on conditional expectations; Markov chains; the Poisson process; continuous-time Markov chains; renewal theory; queuing theory; and introduction to stochastic calculus, e.g., Ito's Lemma. Prerequisite: 26:960:575.         
 
For additional information, contact RU-info at 848-445-info (4636) or colonelhenry.rutgers.edu.
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