Marine port/terminal and landside logistics systems and support facilities. Planning, design, operational efficiency and advanced technologies.

Sustainability concepts and frameworks, design for environment, closed-loop supply chains, sustainability in sourcing, green facilities, renewable energy, facility location and transportation decisions, strategic sustainability implementation. Web registration open only to graduate business and accounting students.

Factors to consider when making sourcing decisions (costs, prices, ethics, globalization); Impact of sourcing on other activities such as product design or inventory management. Open only to graduate business students.

Foundational knowledge for business analytics, including strategies, methods, and tools integrated with hands-on skills for defining business analytics for data-driven decision making and innovation. Online registration open to graduate business and accounting students.

Principles of probability methodology. Application for providing structure to uncertainty. Develop, implement, and use probability models.

Survey of forecasting and time series methods. Models for stationary and nonstationary time series; ARIMA model identification, estimation, and forecast development. Seasonal and dynamic models.

Introduction to data-warehousing, multidimensional database, on-line analytical processing, and survey of business intelligence applications that extract useful information from data warehouses.

Computer-assisted analysis of business data; advanced multiple regression analysis, survey analysis, ANOVA testing for Marketing-type applications and Times Series Analysis methods will be covered.

Overview of highly computational modern statistical learning methods; applications of logistic regression, neural networks, LASSO, trees, boosting and GAM, etc., to finance and marketing data.

Application of Monte Carlo simulation to determine a range of outcomes for all possible courses of action. Application of Excel simulation.

Data cleaning and reshaping; good vs. bad graphics; univariate, bivariate, trivariate, hypervariate, and time series graphics; interactive graphics; web-related computing. Extensive computer applications using R.

Application of decision analysis, simulation and optimization techniques to managerial problems. Learn how to create and present useful spreadsheet models to analyze practical business models.

This course is a core course for the on-campus program and an elective option for the online program.

Emerging technologies transforming the supply chain domain. Topics include: Artificial Intelligence, Machine Learning, Blockchain.

Leveraging large enterprise system applications for strategic value; managing organizational transformation of global enterprises through digital business platforms; coping with disruptive technologies.

SQL; relational database systems; data storage; data manipulation; data aggregation.

NoSQL; semi-structured and unstructured databases; data storage; data manipulation; distributed databases.

Designing and executing business strategies for sustainability (environmental, economic, social/cultural) enabled by digital technologies. Emerging market contexts; team consulting project; international travel.

Managing Business models in digital platform ecosystems; designing new products and services for digital platforms; establishing digital platform leadership; assessing emerging niches in digital spaces.

Acquire, analyze, visualize and perform natural language processing (NLP) on text data. Apply Python, machine learning packages, statistical methodology and computer code to business decision-making.

Fraud detection model systems; identify normal vs. outlying behavior; malicious adversaries; complex datasets; supervised and unsupervised fraud statistical models; measures of model efficacy.

Analytics for supply chain planning. Topics include data-driven decision making, solving real-world problems, utilizing scalable technology, and current industry best practices.

Applications and models of marketing-related data analyses to the development of data-driven marketing strategies and making data-driven marketing decisions.

Decision making under uncertainty using real data applying the most advanced optimization, statistical and probability methods.

Foundation in digital analytics in tandem with digital strategy and solutions through a design thinking approach to working with digital and web data.

Advanced applications of data analytics in dynamic strategy formulation and execution; analytics and business methods for data connected enterprises to continuously enhance their competitive advantage.

How companies can implement 'big data' initiatives to improve business activities. How leading companies have successfully implemented 'big data' initiatives and why some have failed.

Applications of systems theory and concepts, matrix organizational structures, PERT/CPM project modeling, and management information systems to the management of complex and critical projects.

Development of conceptual and analytic skills for improving operations. Analysis of business strategy, formulating and implementing operations strategy, process analysis and design, and project management.

Application of operations management tools and techniques to improve the performance of healthcare delivery systems. May include international travel.

Operational finance for non-finance students. Assessing financial opportunities and challenges, optimizing working capital, managing risk in supply chain finance.

Special topics courses serve as hubs of innovation for new courses covering new trends and recent developments in data sciences, operations management, supply chain management and/or decision support systems.

Deterministic and stochastic demand systems with static/dynamic models. Practice in inventory management, computerized procedures, materials requirements planning, just-in-time production, Kanban systems.

Advanced concepts in production planning and scheduling including resource allocation, lot sizing, flow shop and job shop scheduling, workforce scheduling and assembly line balancing.

Principles of quality management, quality philosophies and frameworks, quality leadership and strategic planning, process management, and performance measurements.

Design and management of engineering teams. Group decision-making, motivation, leadership, infrastructure requirements, performance measurement, team diversity, conflict, and integration.

Strategies and dynamics of deal-making; practical skills necessary to win in a range of business transactions conducted in domestic and international settings. Cases, role-playing, films and simulations.