In addition to the courses listed below, you may choose to take courses in another concentration area as your electives.
ACC 7148 ERP Systems and Business Integration (3 Credits) - Enterprise Planning (ERP) systems are the primary software packages for accounting, operational, and managerial activities of organizations. How ERP systems integrate and coordinate business processes and the management of the organization. Extensive hands-on use of popular software packages for key business activities such as sales, procurement, and production. Prerequisites: BA 7000 with a minimum grade of C and ISM 7500 with a minimum grade of C.
ACC 7280 Accounting Data Analytics (3 Credits) - Introduces concepts, techniques, and software applications used to analyze accounting and related data to support financial decision-making and planning. These data are generated both within and outside the organization. Prerequisite: BA 7000 with a minimum grade of C.
ACC 7290 / ISM 7290 Blockchain: An Accounting and Business Perspective (3 Credits) - Introduces blockchain: a public, transparent, secure, immutable, and distributed ledger. Blockchains can be used to record and transfer any digital asset, not just currency. The course covers the workings, applications, and potential impact of this revolutionary technology. Prerequisite: BA 7000 with a minimum grade of C.
CSC 5050 Algorithms and Data Structures (4 Credits) - Introduction to problem solving methods and algorithm development; data abstraction for structures such as stacks, queues, linked lists, trees, and graphs; searching and sorting algorithms and their analysis.
CSC 5250 Network, Distributed, and Concurrent Programming (3 Credits) - Fundamental concepts and skills of developing networked, distributed, and concurrent applications. Topics include: inter-process communication, TCP/IP sockets programming, remote method invocation, multithreading, concurrency and synchronization. Prerequisites: CSC 4420 with a minimum grade of C- and CSC 4421 with a minimum grade of C-.
CSC 6800 Artificial Intelligence I (3 Credits) - Basic concepts; topics include: recursive problem solving, knowledge representation using semantic networks and frames, state space search methods, planning and problem solving, game playing and adversarial search methods, rules and production systems (RETE networks), constraint satisfaction techniques and applications, optimization algorithms including genetic algorithms, logic programming. Implementation in Lisp and Prolog. Prerequisite: CSC 3110 with a minimum grade of C-.
CSC 6860 Digital Image Processing and Analysis (3 Credits) Review of image formation and acquisition; image transformation; image enhancement and restoration; image compression; morphological image processing; edge detection and segmentation; architecture for image processing.
CSC 7220 Parallel Computing II: Algorithms and Applications (4 Credits) - Problems in parallel algorithms: design, analysis, complexity. Cluster and grid computing: tools, programming, and applications. Prerequisite: CSC 6220 with a minimum grade of C.
CSC 7260 Distributed Systems (3 Credits) - Models of distributed systems, distributed synchronization, algorithms, consistency and replication models and algorithms, fault-tolerance in distributed systems. Prerequisite: 5270 with a minimum grade of C.
CSC 7300 Bioinformatics I: Biological Databases and Data Analysis (3 Credits) - Concepts of bioinformatics; tools for storing and analysis of bioinformatics data. Must be taken with CSC 7301.
CSC 7301 Bioinformatics I: Programming Lab (4 Credits) - Hands-on experience and exercises for CSC 7300/MBG 7300 lectures.
ECE 7610 Advanced Parallel and Distributed Systems (4 Credits) - Advanced topics in parallel and distributed computing, multicore and parallel architecture, communication, synchronization, parallel algorithms and programming, load balancing and scheduling, security. Prerequisite: ECE 5610 or ECE 5650.
ECO 7100 Econometrics I (4 Credits) - Probability and statistics: moment generating functions, common families of statistical distributions, multiple random variables and properties of a random sample. Estimation and hypothesis testing: method of moments, generalized method of moments, maximum likelihood estimators, instrumental variable estimators, Bayes estimators, likelihood ratio tests, finite sample properties and asymptotic properties of OLS. Prerequisites: ECO 6100 with a minimum grade of C and ECO 7020 with a minimum grade of C.
ECO 7110 Econometrics II (4 Credits) - Modeling and estimation: generalized least squares, panel data models (fixed effects and random effects), system of equations (endogeneity, identification), models with discrete dependent variables (probit, logit), models with limited dependent variables (truncation, censoring), stationary time-series (ARMA), vector-autoregression (VAR, VMA), non-stationary time-series (unit roots, cointegration). Prerequisite: ECO 7100 with a minimum grade of C.
ECO 7120 Econometrics III (4 Credits) - Advanced economic techniques in microeconomics and macroeconomics. In the first half of the course, emphasis on specification, estimation, interpretation, and testing of microeconomic models. The second half will cover statistical models for the analysis of economic time series data, with applications in macroeconomics and finance. Prerequisites: ECO 7100 with a minimum grade of C and ECO 7110 with a minimum grade of C.
IE 7325 Supply Chain Management (4 Credits) - Fundamental theories and concepts in design and management of supply chains. Theories and applications of mathematical models in SCM. Logistics, advanced strategic and tactical planning, extended enterprise integration.
IE 7720: Engineering Risk and Decision Analysis (4 Credits) - Structure, modeling and analysis of technical management decisions with emphasis on multiple objectives and trade-offs, and significant uncertainty. Explores barriers to rational decision making.
IE 7860 Intelligent Analytics (Neural Networks & Deep Learning). (3 Credits) - Computational intelligence methods used to solve complex analytics problems and develop decision support systems. Project-centric approach with the goal of developing several analytics solutions for real-world problems. [Syllabus]
ISM 7570 Data Mining (3 Credits) - Tools and techniques used to analyze large data bases; hands-on approach to common techniques. Emphasis on application of data mining to problems in marketing, finance, and other business disciplines.
ISM 7996 Principles for Customer Relationship Management (3 Credits) - Investigation of the antecedents and consequences of implementing a customer-relationship management strategy. The course will provide students with insight on: What CRM and its conceptual foundations are; How CRM forces the interaction between corporate strategy, organizational structure, supply chain, and customer facing front end; The role of measuring and managing customer satisfaction, customer loyalty and customer profitability; Hands-on application with salesforce.com.
ISM 8000 Application Development with Swift (3 Credits) - This course will establish a foundation for understanding the value of mobile applications in the enterprise and how to design, create, and publish mobile applications for the Apple iOS using Swift and Xcode. These tools allow you to quickly develop a mobile application so you can focus your energy on your
design. Elective credit for data-driven business track ONLY.
STA 5830 Applied Time Series (3 Credits) - Time series models, moving average models, autoregressive models, non-stationary models, and more general models; point estimators, confidence intervals, and forecast in the time domain. Statistical analysis in the frequency domain; spectral density and periodogram. Prerequisites: MAT 5700 with a minimum grade of C- and MAT 5800 with a minimum grade of C-.
STA 6840 Linear Statistical Models (3 Credits) - Multivariate linear regression models, examples; least square estimates and system of normal equations; the Gauss-Markov theorem; hypothesis testing about regression coefficients; confidence intervals and regions; prediction; model selection, stepwise regression. Analysis of variances (ANOVA). Prerequisites: MAT 5700 with a minimum grade of C- and MAT 5800 with a minimum grade of C-.