This course provides an executive viewpoint of marketing concepts, such as branding and segmentation, for strategic and organizational decision-making. There is an emphasis on tools available for analysis and control of marketing activities, including the use of new media. Topics also include industrial life cycles, customer experience, and pricing strategy.

This course will develop a student?s mastery of cutting-edge project management techniques in Agile and Scrum methodologies, technologies, and toolkits. The student will be able to successfully develop and manage Agile teams, apply sound judgement to appropriate method implementation, ensure project outcomes, and influence business stakeholders. The course will include practical experiential learning, in a teams-based setting, to lead and demonstrate various Agile and Scrum tools and techniques.

This graduate course provides comprehensive coverage of project management, focusing on the methods and competencies needed to effectively manage projects. Upon successful completion of this course, students will be able to understand different project management techniques, terminology and trends; define project success measures and methods; improve quality, cost and efficiency with the project management process; and gain basic competency using project management software.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications.

This course will cover an overview of financial technology and its various applications. The specific topics include fintech and financial service, cryptocurrencies, high-frequency trading, peer-to-peer lending, etc. The course will help students learn fintech industry through case studies. It also provides students with a unique opportunity to delve deep into one aspect of financial technology and write an extensive paper/report on this topic. Topics include (but are not limited to): Data-driven credit models, Cryptocurrencies, Digital wallets, Blockchain and its applications, Financial cloud services, Robo advising, Crowd-funding, Peer-to-Peer lending, High-frequency trading, Payments, Artificial Intelligence, Digital banking, Defi (Decentralized Finance), NFT, etc.

This course will cover an overview of financial technology and its various applications. The specific topics include fintech and financial service, cryptocurrencies, high-frequency trading, peer-to-peer lending, etc. The course will help students learn fintech industry through case studies. It also provides students with a unique opportunity to delve deep into one aspect of financial technology and write an extensive paper/report on this topic. Topics include (but are not limited to): Data-driven credit models, Cryptocurrencies, Digital wallets, Blockchain and its applications, Financial cloud services, Robo advising, Crowd-funding, Peer-to-Peer lending, High-frequency trading, Payments, Artificial Intelligence, Digital banking, Defi (Decentralized Finance), NFT, etc.

This course provides an overview of statistical analysis and inference. The language and methods of statistics are used throughout the MBA curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing as well as media reporting, both inside and beyond the business community. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary. The course has an emphasis on business applications.