Courses

The listing of a course description here does not guarantee a course’s being offered in a particular term. Please refer to the published schedule of classes on MyBU Student Portal for confirmation a class is actually being taught and for specific course meeting dates and times.

• MET AD 649: Agile Methods for Technical Innovation and Engineering Management
  Prerequisite: MET PM 100 Lab - In this course, you will gain an understanding of how new Agile principles and practices are changing the landscape of project management and be provided a fresh insight into how to successfully blend Agile and traditional project management principles and practices in the right proportions to fit any business and project situation. You’ll also gain a deep understanding of Agile project management principles and practices in order to see them as complementary rather than competitive to traditional project management. Topics include: Agile fundamentals, principles, and practices; roots of Agile in TQM and Lean Manufacturing; adapting an Agile approach to fit a business environment; planning and managing an enterprise-level Agile transformation; integrating AI into Agile; and scaling Agile to an enterprise level using Agile frameworks and Agile project management tools.
• MET AD 650: Economic Development via Tourism in the Developing World
  Many branches of the tourism industry have become incorporated into the increasingly important economic paradigm of sustainable economic development (economic development while minimizing the negative environmental, social and cultural impact of such development) in both the developed and developing world. In this course students will visit a developing country and learn how the tourist industry has developed in that country, determine how sustainable that development has been and what are potential directions for future growth in the tourist industry.
• MET AD 654: Marketing Analytics
  Prerequisite: MET AD 571. Become familiar with the foundations of modern marketing analytics and develop your ability to select, apply, and interpret readily available data on customer purchase behavior, new customer acquisition, current customer retention, and marketing mix optimization. This course explores techniques to support the managerial decision-making process and skills in using state-of-the-art statistical and analytics tools. Students will gain a basic understanding of how transaction and descriptive data are used to construct customer segmentation schemas, build and calibrate predictive machine learning models, and quantify the incremental impact of specific marketing actions. Python and Tableau are used in this course. No prior Python experience is required.
• MET AD 667: Innovation, Global Competitiveness, and National Economic Development
  Examines various approaches to developing high tech innovation based economies as a route to self sufficiency and growth. Factors studied include both structural reforms in the political, legal and economic areas, and government sponsored initiatives in higher education, basic research, private venture capital, grants to support new product development by promising ventures, and the creation of science and technology parks and incubators. Students independently research, write, and present studies of the strategies of various countries. This will be augmented by case studies, reading, and guest speakers on strategies being employed in such countries as Taiwan, Thailand, and Brazil.
• MET AD 675: Technology and Innovation in Construction Projects
  Corequisite: MET PM 100 Lab. - This foundational course provides a comprehensive look at the Construction 4.0 paradigm, the design, development, construction, management, and operation of built environment assets. It emphasizes the synergy between the digital aspects, like Building Information Models (BIM) and Common Data Environment (CDE), with infrastructure and the physical aspects of assets, leveraging cyber-physical systems, IoT, AI, data, and services. The curriculum is built around two main pillars: adopting advanced technologies and integrating project and process enablers and lean principles. This approach ensures efficient asset lifecycle management and prepares students for the technological and procedural advancements in the construction industry. This course will align with the goals of PMI's Construction Professional in Built Environment Projects (PMI-CP) credential.
• MET AD 676: Construction Project Cost and Risk Management
  Corequisite: MET PM 100 lab - This course provides a comprehensive and forward-looking exploration of construction cost and risk management practices essential to delivering successful built environment projects in the digital age. Students will study the principles of cost control, budgeting, change management, and lifecycle costing while integrating advanced risk management strategies. Special emphasis is placed on identifying and mitigating procurement risks, managing claims and disputes, aligning contract models with risk allocation, and addressing interface management (IM) as a key contributor to risk in complex projects. Students will also explore how artificial intelligence, predictive analytics, and digital simulation tools reshape forecasting, scenario planning, and risk-informed decision-making. The course includes practical exercises, case studies, and simulations replicating industry scenarios that align with the PMI-CP certification objectives.
• MET AD 677: Digital Twins for Projects and Infrastructure
  Corequisite: MET PM 100 lab - The course introduces students to Digital Twin technologies and AI, transforming project management through real-time monitoring, predictive modeling, and automation. Students will explore how Digital Twins integrate real-world data with AI-powered simulations to enhance project planning, asset management, and risk mitigation. The curriculum covers AI-driven decision-making, intelligent scheduling, and automated reporting, equipping students with practical skills for optimizing project execution across industries such as construction, energy, smart cities, and infrastructure. By bridging theory and application, this course ensures students are prepared to lead AI-enhanced projects and large-scale digital asset management.
• MET AD 678: Financial Regulation and Ethics
  Financial Regulation and Ethics is a course designed to thoroughly review the important topics of financial regulations, policies, and ethics. The course will explore an overview of the financial systems, their history, problems, and issues for the purpose of understanding the enactment of regulations as a method to protect the financial systems and investors. Also, regulators and their authority will be identified, both domestically and internationally. Ethics, an extremely important aspect of finance will be discussed and explored. Ethics is a difficult topic to define and can be impacted by social norms. During the ethics portion of the course, students will study where ethics have failed and caused major issues for the financial marketplace and individual companies.
• MET AD 680: Global Supply Chains
  This course covers the quantitative analysis tools to support operations management for a supply chain that is geographically dispersed and culturally diverse. The tools necessary to assure that the products/services are delivered/provided in the quality and timely manner include demand forecasting, inventory and capacity buffer optimization, delayed differentiation, statistical risk pooling, and stochastic inventory optimization. These tools are applied to decisions such as offshoring, multi-country outsourcing, push-pull, reverse supply chains, and risk mitigation. Particular attention is given to sustainability, information technology and digitalization, and creating resiliency.
• MET AD 682: Risk Assessment and Security Management
  The course reviews the management issues involved with security and risk analysis. Topics include risk identification, risk management and alternative response actions. Security is analyzed from the numerous perspectives to nclude: infrastructure, employee, visitor and computer systems. Security is resented from the levels of the: firm as well as the local, state and national environment. Focus is on the proactive investment of resources to develop a comprehensive plan that identifies the elements of security and risk analysis as well as presents options for risk mitigation.
• MET AD 685: Quantitative Methods for Finance
  Prerequisite: MET AD 100 Lab. Finance is a highly competitive and dynamic industry that demands quantitative-oriented professionals. This course equips students with empirical techniques which are used in the analysis of financial markets, with a strong focus on financial applications using actual data. The goal of this course is to provide students with a number of econometric techniques which are used in the analysis of financial markets based on asset pricing and corporate finance models. In particular, the emphasis is on classical linear regression models, time series analysis, and limited dependent variable models applied to the following topics: predictability of asset returns; event study analysis; econometric tests of the CAPM and multifactor models; and volatility modeling.
• MET AD 688: Big Data and Cloud Analytics for Business
  Prerequisite: MET AD571 Work with large, complex datasets beyond traditional desktop analytics using Apache Spark (PySpark), DuckDB, Polars, SQL-based data warehousing, and AWS cloud services. You will explore SQL databases through AWS’ Relational Database Service (RDS), learn to build feature engineering pipelines, and scalable machine-learning workflows using Spark MLlib. Key topics include cloud computing parallel processing, management of massive data stores, cloud data architectures, web scraping, API-based data collection, text and web mining, and batch and streaming analytics. You will develop an end-to-end analytics solution from data ingestion and cleaning to modeling, evaluation, and communication, using Python (PySpark), SQL, Git, and GitHub in a cloud-ready AWS environment. By the end of the course, you will be able to design scalable analytics pipelines, manage cloud data environments, and apply distributed machine learning to real-world datasets. The course culminates in a term project implementing a complete big data and cloud analytics workflow.
• MET AD 690: Supply Chain Logistics
  This course covers quantitative approaches to logistics management. It teaches network optimization techniques and center gravity models for location analysis, mathematical programming for selecting the optimal transportation modality, statistical distributions for modeling the statistical uncertainty around the arrivals of trucks to a warehouse or a store, and inventory modeling for optimizing distribution centers. The course introduces mathematical models for warehouse layout decisions, learning curve models, and logistics network design in the context of today's increasingly digitalized supply networks.
• MET AD 698: Applied Generative AI for Business Analytics
  Corequisite: MET AD 100 Lab. This course is designed for analytics developers and advanced business students seeking to build practical, production-ready Generative AI (GenAI) Applications. Emphasizing hands-on learning, students will explore key techniques such as, Natural Language Processing, Recurrent Neural Networks and Transformer Architectures, prompt engineering, in-context learning (ICL), retrieval-augmented generation (RAG), Agentic Artificial Intelligence, and responsible AI design. Students will work with open-source tools and APIs including LangChain, LlamaIndex, and embedding models, while learning to implement GenAI systems across the entire development lifecycle — from prompt design and knowledge retrieval to fine-tuning and deployment. This course bridges the gap between business analytics fluency and technical AI development, equipping students to build domain-specific LLM applications that solve real-world problems.
• MET AD 699: Data Mining for Business Analytics
  Prerequisites: AD571 Enterprises, organizations, and individuals are creating, collecting, and using a massive amount of structured and unstructured data with the goal of converting the information into knowledge, improving the quality and the efficiency of their decision-making process, and better positioning themselves in the highly competitive marketplace. Data mining is the process of finding, extracting, visualizing, and reporting useful information and insights from both small and large datasets with the help of sophisticated data analysis methods. It is part of business analytics, which refers to the process of leveraging different forms of analytical techniques to achieve desired business outcomes through requiring business relevancy, actionable insight, performance management, and value management. The students in this course will study the fundamental principles and techniques of data mining. They will learn how to apply advanced models and software applications for data mining. Finally, students will learn how to examine the overall business process of an organization or a project with the goal of understanding (i) the business context where hidden internal and external value is to be identified and captured, and (ii) exactly what the selected data mining method does. Python, R, SQL, and Power BI software are used in this course.
• MET AD 709: Case Studies in Current Corporate Financial Topics
  Prerequisite: MET AD 522. The course will help you to leverage what you have learned in both accounting and finance and apply that knowledge to current issues in the business world in areas such as Business Ethics; Corporate Responsibility, ESG & Responsible Investing; Risk Management; Financial Forecasting; Cost of Capital & Rate of Return; Organic Growth Strategies; Valuation; Mergers & Acquisitions; Turnarounds and Bankruptcies.
• MET AD 712: Financial Markets and Institutions
  Investigates and analyzes organization, structure, and performance of US money and capital markets and institutions. Examines regulation of the financial industry and the role of financial instruments.
• MET AD 713: Derivative Securities and Markets
  Prerequisite: MET AD 522. The course will help you to leverage what you have learned in both accounting and finance and apply that knowledge to current issues in the business world in areas such as Business Ethics; Corporate Responsibility, ESG & Responsible Investing; Risk Management; Financial Forecasting; Cost of Capital & Rate of Return; Organic Growth Strategies; Valuation; Mergers & Acquisitions; Turnarounds and Bankruptcies.
• MET AD 714: Mergers and Acquisitions
  Prerequisites: MET AD 522. This course examines the corporate valuation process by which takeovers and other corporate control transactions take place. It includes financial forecasting, based on expectation models, scenario analysis, and due diligence. Of particular interest will be the defensive measures by management against hostile bids, buyout transactions, the relation of takeovers to capital structure changes, and the insider trading in takeover contests.
• MET AD 715: Quantitative and Qualitative Decision-Making
  The purpose of this course is to help improve business problem solving and managerial decision-making through the use of quantitative and qualitative decision-making tools and techniques. This course will provide the student with an overview of how decisions are made to solve management problems in the business environment. It introduces the fundamental concepts and methodologies of the decision-making process, problem-solving, decision analysis, data collection, probability distribution, evaluation, and prediction methods. Students will learn how to apply different quantitative and qualitative analytical tools commonly used in business to provide a depth of understanding and support to various decision-making activities within each subject area of management. Through the use of case studies of decisions made by managers in various production and service industries and a business simulation package specifically prepared for this course, the scope and breadth of decision-making in business will be described.