Bharatendra Rai

MIS 101: The Business Organization

A technology-based, cross-discipline course for first-year students, the first business core course. It introduces first-year business majors to the world of business and enriches their first year experience. It provides students with an overview of business, its environment and its subsystems (e.g. operations, marketing, accounting, finance and information systems); and enhances their computer and team-working skills. Through informational and advising experiences students make decisions in areas such as the selection of courses, a major, a career and the utilization of on-campus student resources.

MIS 101: The Business Organization

A technology-based, cross-discipline course for first-year students, the first business core course. It introduces first-year business majors to the world of business and enriches their first year experience. It provides students with an overview of business, its environment and its subsystems (e.g. operations, marketing, accounting, finance and information systems); and enhances their computer and team-working skills. Through informational and advising experiences students make decisions in areas such as the selection of courses, a major, a career and the utilization of on-campus student resources.

POM 212: Business Statistics

Examines both descriptive and inferential statistics as applied to business. Topics include graphical and tabular methods of data presentation, probability theory and distributions, hypothesis testing, analysis of variance, regression and forecasting. Emphasis is placed on concepts, applications, and the proper use of statistics to collect, analyze, and interpret data. Throughout this course students will use computer software to perform statistical analyses. Students will learn how to make decisions using facts and the techniques of data analysis. Students will also use the internet to supplement classroom learning.

POM 415: Applied Decision Techniques

Manufacturing and service applications of selected analytical decision-making tools and techniques. The course illustrates, by example, how manufacturing and service operations can apply quantitative tools to decisions involving queuing, staffing, scheduling, product mix planning, and inventory control.

POM 681: Business Analytics&Data Mining

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.

POM 681: Business Analytics&Data Mining

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.

POM 681: Business Analytics&Data Mining

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.

POM 333: Intro to Business Analytics

Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.

POM 333: Intro to Business Analytics

Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.
Register for this course.

POM 415: Applied Decision Techniques

Manufacturing and service applications of selected analytical decision-making tools and techniques. The course illustrates, by example, how manufacturing and service operations can apply quantitative tools to decisions involving queuing, staffing, scheduling, product mix planning, and inventory control.
Register for this course.

POM 333: Intro to Business Analytics

Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.
Register for this course.

MIS 381: Introduction to Cybersecurity

A comprehensive overview of cybersecurity issues and current best practices in several applicative domains. The course discusses emerging cybersecurity threats and available countermeasures with respect to the most recent information technologies, including access control, cryptography, and protections of wired & wireless networks & data systems. The course presents current trends & open problems in cybersecurity.
Register for this course.

POM 681: Business Analytics&Data Mining

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.
Register for this course.

POM 333: Intro to Business Analytics

Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.
Register for this course.

POM 681: Business Analytics&Data Mining

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.
Register for this course.