Bachelor of Science in Business Data Analytics Online

The Data Ethics and Privacy course provides students with a solid understanding of the ethical and privacy implications associated with collecting, analyzing, and using data in various contexts. The course explores the ethical challenges arising from data-driven decision-making, data sharing, algorithmic bias, and the responsible use of personal information. Students examine the legal and regulatory frameworks related to data privacy, along with ethical guidelines and best practices. The course also addresses the social and cultural implications of data use, emphasizing the need for ethical decision-making and responsible data practices.

The Programming for Data Analytics course is designed to provide students with the necessary programming skills to manipulate, analyze, and visualize data effectively. The course focuses on teaching a programming language commonly used in data analytics, such as Python or R, and introduces students to various libraries and tools specifically designed for data manipulation, analysis and visualization. Through hands-on programming exercises and projects, students develop proficiency in writing code to handle data, ability to extract insights, draw meaningful conclusions from datasets and apply analytical techniques.

The Big Data Analytics course provides students with the knowledge and skills required to analyze and derive insights from large and complex datasets. The course explores the concepts, techniques, and tools used in processing, managing, and analyzing big data. Students learn how to handle the challenges posed by the volume, variety, and velocity of big data. They also gain practical experience in using popular big data technologies and platforms for data processing and analysis.

The Data Visualization course introduces students to the principles, techniques, and tools used in visualizing and communicating data effectively. The course focuses on developing the skills necessary to transform complex datasets into visually appealing and informative visualizations. Students learn about different types of visualizations, data representation techniques, and the principles of visual design. They also gain hands-on experience using popular data visualization tools and libraries to create interactive and engaging visualizations.

The Statistics for Data Analytics course provides students with a solid foundation in statistical concepts and techniques essential for data analysis and interpretation. The course provides students with the necessary statistical tools to make informed decisions and draw meaningful insights from data. By learning statistical concepts, techniques, and use of software tools, students gain the skills to apply statistical methods effectively in various data analytics contexts.

This course provides students with a comprehensive understanding of forecasting techniques and their application using Microsoft Excel. Students will learn how to analyze historical data, identify patterns, and develop accurate forecasts for decision-making. Through a combination of lectures, hands-on exercises, and case studies, students will gain practical skills in applying forecasting models using Excel.

This course introduces students to the fundamental concepts and techniques of business analytics using Microsoft Excel. Students will learn how to use Excel as a powerful tool for data analysis and decision-making in a business context. Through hands-on exercises and projects, students will gain proficiency in using Excel functions, formulas, and tools to analyze and visualize data, derive insights, and make informed business decisions.

The Data Warehousing and Database Management course provides students with a solid foundation in the principles and techniques of data warehousing and database management concepts, involved in designing, implementing, and managing data warehouses and databases. The course explores the importance of data management in modern organizations and focuses on the design and optimization of database systems for efficient data storage, retrieval, and analysis. Students learn about data modeling, data warehousing architectures, data integration, and various techniques for managing and querying databases. By learning about data modeling, database design, data integration, and database optimization, students gain the skills necessary to design and manage efficient and scalable database systems to support organizational decision-making and analytics.

This course provides students with an understanding of the principles, practices, and strategies involved in data governance and management. Students will learn how to effectively manage data assets within organizations, ensure data quality and integrity, establish data governance frameworks, and comply with regulatory requirements. Through a combination of lectures, case studies, and practical exercises, students will gain knowledge and skills to implement data governance practices in real-world scenarios.

The Time Series Analysis course introduces students to the theory and techniques used to analyze and model time-dependent data. Time series data is prevalent in various fields such as finance, economics, engineering, and environmental sciences. This course equips students with the skills to understand, interpret, and forecast time series data, enabling them to make informed decisions and predictions based on historical patterns. Students also gain proficiency in using software tools to analyze and model time series data, preparing them for careers in data analysis, finance, forecasting, and related fields.

The course aims to familiarize students with the fundamental concepts, techniques, and tools used in analyzing and interpreting data for decision making purposes. Through a combination of lectures, hands-on exercises, and case studies, students gain a solid understanding of the data analytics process from data collection to data analysis.

This course explores the major theories and applications that explain international business transactions and the institutions influencing those activities. It studies the social, cultural, political and regulatory environments within which international business transactions take place; the foreign exchange systems which facilitate or constrain such transactions; and the dynamics of international business government relationships.

This is a capstone course for seniors in the business program. The course provides a framework for problem identification and strategy formation within organizations. Emphasis will be placed on the interplay of judgment and decision making, the use of both qualitative and quantitative factors in policy formulation and execution and the impact of social and moral values. The course provides an opportunity for students to integrate and apply previously acquired knowledge in the areas of accounting, economics, finance, marketing, and management. Utilizes the case approach as well as readings from other disciplines.

This course is an overview of commercial law with emphasis on the law of contracts, sales, property, partnerships and corporations, commercial paper, secured transactions, bankruptcy and protection of intellectual property.

This is a course in marketing designed as part of the University’s Core Curriculum. The course is a study of the basic principles and concepts in the marketing process, the techniques of market research, and the function of advertising in business operations, the role it plays in the economy, as well as a consideration of the sociological and ethical aspects of current practices.

This is a course in management designed as part of the University's Core curriculum. It is an introduction to the principles of business management: planning, organizing, staffing, directing, and controlling of businesses. The course combines the traditional management process approach with contemporary systems and behavioral approaches.

This course is an introduction to the basic concepts, practices, terminologies, and theories of financial management. It provides an overview of financial management as central to the operation of a business enterprise: planning the firm’s needs for funds, selecting the least costly source and allocating their use to maximize value of owner’s investment. Topics include: ratio analysis of financial statements, yield curves and rates of return, and the measurement of the risk of financial assets.

This course is a survey of computer information systems and how they relate to administration and management in the modern business organization. Topics include choosing the right system for the office environment, site selection and preparation, types of software and their applications, integration of hardware and software, networking techniques and theory, centralized versus decentralized and networked information systems, network topologies, information location and retrieval through the Internet and the World Wide Web, message exchanging through email, message privacy techniques incorporating public key/private key encryption, and emerging trends in information systems.

This course is an examination of the principles of personnel administration and processes of recruitment, placement, development, evaluation, compensation, and effective utilization of the firm’s human resources. Case studies are utilized.

Business and econometric modeling techniques are examined through the use of Windows-based microcomputer spreadsheet construction and analysis. Emphasis is placed upon practical application in the business environment. Topics include inventory simulation, capital budgeting, decision analysis, break-even analysis, database management and record keeping, and single and multiple linear regression analysis (3 credits).

This course is an introduction to the concepts and applications of business analytics. Most companies today collect an overwhelming amount of data. However, gaining insight from analytics continues to elude many organizations. Business analytics requires individuals to be knowledgeable in the fundamentals of business (e.g. knowing the right questions to ask) as well as an array of disciplines from information systems, machine learning, and statistics. To help meet the market demand for analytics professionals, this course provides students with an analytical toolset that enables them to address data-driven business problems. The course features case studies and hands-on approaches to demonstrate the analytics concepts and techniques used in the business world. The course makes use of the leading business analytics tools: R and R Studio. We discuss supervised and unsupervised machine learning techniques for predictive and descriptive analytics.

This course is an introduction to the basic concepts, terminology, and principles of the American legal system. Topics include: civil dispute resolution, constitutional law, administrative law, criminal law, intentional torts, negligence, introduction to contracts, mutual assent, illegal bargains, contract in writing, contract remedies, performance, breach and discharge.

The course introduces the student to the basic economic principles and analytical techniques that are necessary to understand how the market economy functions and what market efficiency means. It explains why the government intervenes and how such intervention affects the market. It focuses on the study of the behavior of individual economic units, which include consumers, investors, business firms, workers, and other entities that play a role in the functioning of the economy. The course examines how and why these units make economic decisions, and how they interact to form larger units — markets and industries. As an introductory course, it is designed to equip the students with the basic tools of economic analysis that will help them understand better the world we live in.

This course is a survey of frequently used stochastic and deterministic quantitative methodologies used in the management of business organizations and the allocation of scarce resources. Topics and applications include linear programming with graphical and simplex solving, transportation, transshipment, assignment, network models, project management techniques, inventory theory, simulation, queuing, forecasting, and decision theory. Computer-based software tools for management decision-making are integral to the course.