31 courses with the subject BUAN, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
BUAN 167AI Essentials for Business Applications3
This course introduces students to the practical applications of artificial intelligence in the modern business world. Through hands-on exercises, case studies, and real-world examples, students will learn to identify and leverage AI tools to analyze data, automate tasks, generate creative content and improve productivity. The course will also address ethical considerations, limitations, and the social impact of AI.
BUAN 205Introduction to Programming for Business Applications3
Introduction to computer programming and data analysis utilizing an object-oriented programming language. Topics include input/output statements, variables, arithmetic and logical operations, decision statements, loop structures, functions, data formats (csv, json, xml), web scraping and libraries for data manipulation/analysis. In this course, problem solving and algorithm development skills will be honed on assignments involving business applications. O'Malley School of Business students can take this course to satisfy a three credit Liberal Arts Elective requirement.
Applications of statistical methods of data analysis and decision making. Coverage includes descriptive statistics, statistical measures and estimation, testing of hypothesis, linear regression and correlation analysis. Use of computer software for statistical analysis and business applications. Prerequisite: MATH 153 (or MATH 105, MATH 185), MATH 154 (MATH 106, MATH 186), CIS 110.
This course covers examples of descriptive analytics, predictive analytics, and prescriptive analytics. Topics include, data identification, preparation and representation; risk analysis and simulation; project management; decision analysis; and optimization. The course provides a balance between understanding processes for analytical modeling and developing the tools to represent and solve decision making problems. It introduces students to the fundamental concepts and tools needed to understand the emerging role of business analytics in organizations and shows students how to apply basic business analytics tools in a spreadsheet environment, and how to communicate with analytics professionals to effectively use and interpret analytic models and results for making better business decision. Emphasis is placed on applications, concepts and interpretation of results. Prerequisites: BUAN 227.
This course introduces the core concepts of data and information management. It is centered around the core skills of identifying organizational information requirements, modeling them using conceptual data modeling techniques, converting the conceptual data models into relational data models, and implementing the models using a commercial relational database management system. Additional topics include database administration, security, transaction management, distributed databases and SQL programming. Prerequisite: CIS 110.
This course introduces the core concepts, principles and technologies that are utilized to visualize data. Students will learn about that different dimensions of data, how different types of data are encoded and how to analyze, summarize and visualize data. Spreadsheet-based and web-based visualization tools will be utilized throughout the course. Pre-requisites: BUAN 227, BUAN 205/CIS 205.
BUAN 327Regression & Forecasting Modeling for Business Applications3
The course aims to broaden students' knowledge of statistics as an instrument for extracting information from data and a basis for enhanced decision-making in every aspect of business. Topics include regression analysis, time series forecasting, Analysis of Variance (ANOVA), and design of experiments.
Supply chains are an integral part of contemporary business practices. This course focuses on understanding key areas of logistics and supply chain management where data analytics can help the companies overcome the complexities of today's marketplace. Students will be introduced to various methods and tools for descriptive, predictive and prescriptive analytics to address supply-chain decision problems such as efficiently managing the network of suppliers, manufacturers of goods/services, and distributors. Much of the course concepts will be covered through case studies and simulations. This course may not be taken concurrently with MGMT 307. Pre-requisite: BUAN 227.
BUAN 375Assimilating the Internship Experience in Business Analytics3
In consultation with the faculty advisor, students design and complete an independent project related to their BUAN internship. This project aids in assimilating a practical off-campus work experience in business, industry, government or cultural organization with the students' studies and/or career interests. This course is subject to the approval of the Department Chair, Dean, and Internship Coordinator of the School of Business. The student is required to pre-register with the Internship Coordinator and to obtain internship placement prior to the start of the semester. (Free elective).
This course examines the legal and regulatory framework for current privacy laws in the United States. Students study industry-specific privacy laws and practices in the healthcare, financial and education sectors, as well as privacy in the workplace. The course addresses provisions limiting government access to private information and discuss laws regulating the ability of third parties to access such information. The course examines policies governing data retention and explores the potential liability and reporting requirements of an organization following a data breach. The course covers the protection of privacy and personal data internationally, including the European Union General Data Protection Regulation. Emerging privacy and data protection issues arising from new technological developments are also addressed.
This course addresses how technology can be used to connect data to decision making. The use of real-world examples and cases places data mining techniques in context and fosters the development of data-analytic thinking, and also illustrates the proper application of data-mining techniques is as much an art as it is a science. In addition to the cases, the course features hands-on exercises within data mining software. Prerequisites: BUAN 227 and CIS205 or BUAN205.
BUAN 416Information & System Security for Business Analytics3
This course covers the tools, techniques and issues related to securing digital information and systems. Topics include authentication, anonymity, basic cryptographic tools, access management, web tracking technologies and digital rights management. Issues will be examined from both the business owner and user perspective. Prerequisite: BUAN 205 or CIS 205.
BUAN 420Introduction to Blockchain, Smart Contracts & NFT's3
The goal of this course is to introduce students to blockchain, smart contracts and non-fungible tokens (NFTs), to understand their functionality, benefits and challenges. Blockchain is an immutable distributed/shared ledger technology that is radically transforming a range of business models. Understanding blockchain fundamentals and designing solutions using it along with supporting technologies will be vital for both technical and business professionals. Through lectures, lab sessions, and projects, this course will help students understand how to use blockchain to make business decisions and will develop solutions using blockchain and the Ethereum platform. Prerequisite: CIS 205 or BUAN 205 or CMPT 342 or CMPT 102.
BUAN 427Artificial lntelligence and Machine Learning3
This course focuses on applying and programming Machine Learning (ML) algorithms to build Artificial Intelligence (AI) systems. ML, a subfield of AI, includes concepts and techniques such as Deep Learning, Supervised and Unsupervised learning, Neural Networks, K-Nearest Neighbors (KNN) classification, Support Vector Machines (SVM), and logistic regression to solve data-intensive business problems. Students will be expected to design and implement a data driven solution to a real-world business problem.
BUAN 440Big Data Analytics for Business Analytics3
This course introduces the student to the fundamental concepts of Big Data management and analytics. This course will examine the challenges faced by applications dealing with very large volumes of data as well as in proposing scalable solutions for them. Modern big data technologies such as current map-reduce and NoSQL platforms will be ultilized to solve large business analytics problems. Pre-requisite: BUAN 410 and BUAN 427.
This course exposes students to evolving techniques and theories on issues of current professional interest in information system development and practice. Topics may include network design and management, software engineering computer and network security, ethical, global and legal issues of information systems. Prerequisite: varies according to topic.
A program of supervised reading and research under the direction of a member of the Department. Topics and methods of research are to be developed in consultation with the supervising professor. Open to qualified students who meet the departmental requirements and have the approval of the Department Chair and the Dean.
This course examines foundational privacy concepts and provides an overview of the legal and regulatory frameworks for current privacy laws. It explores sector-specific legislation in the U.S. and examines the differing legal requirements for handling and transferring data under the General Data Protection Regulation (GDPR). The course examines appropriate data governance practices and discusses how organizations devise privacy and data protection strategies. The course will use real-life case studies to examine the sufficiency of data protection measures used by organizations and will explore the potential liability and reporting requirements following a data breach. Students will learn consistent methods for applying privacy principles to emerging technologies in the areas of biometric data and artificial intelligence.
The course provides an understanding of the different data types and their encoding schemes. Learn data visualization principles and Mantra(s). Learn how to tell a story through data. Learn how to extract insight through data, utilize current visualization computing platforms to provide insight. The course emphasizes, sound User Interface (UI) as well as User Experience (UX) Principles. Prerequisite: BUAN 605.
BUAN 610Data Mining Methods for Business Analytics3
In this course, students learn how to make sense out of data (Gather, Ingest, Store, Analyze, visualize train-models and Mine) for the purpose of decision support. Topics covered: Data Gathering, Repurposing Data, Descriptive Analytics, Outlier(s) Detection, Similarity Measures and Cluster Analysis, Classification & Prediction (Entropy, SVM, Naïve Bayes), Association Rules, Regression Analysis, Time Series Forecasting, Social Media Analytics and Text Mining. Generative AI Architecture(s) and platforms will also be introduced.
BUAN 611Advanced Statistical and Predictive Modeling for Business Analytics3
This course focuses on advanced statistical modeling techniques and their applications in business analytics. The curriculum emphasizes time series analysis, experimental design, advanced regression methods, and multivariate analysis. Students will use R and Python for real-world business problem-solving, with an emphasis on predictive modeling and the automation of data processes. The course concludes with a capstone project, providing hands-on experience with business case analysis and advanced forecasting techniques. Prerequisite: BUAN 510.
Data analytics have transformed how business executives make strategic decisions. Decision-makers now rely heavily on sophisticated quantitative analysis using the user-friendly environment of spreadsheet software, such as Microsoft Excel. This course introduces students to quantitative modeling for strategic decision-making across various business areas, including finance, marketing, and operations. Topics include decision-making under uncertainty, revenue management, simulation, and mathematical programming. While Excel will be used, the course focuses on understanding, structuring, and solving business problems and interpreting and communicating the solutions effectively in a realistic business context.
This is a Data Engineering Course. It covers the fundamentals of sound database design, storing, manipulating and retrieving data, Conceptual Data Modeling, SQL, Functional Dependencies and Data Normalization, transaction management, transferring data between Excel and csv and SQL-engines. JSON formats as well as NoSQL Concepts.
BUAN 627Advanced Machine Learning and Artificial Intelligence for Business Analytics3
This advanced graduate course provides a rigorous and in-depth exploration of machine learning (ML) and artificial intelligence (AI) frameworks for solving complex business problems. Building on foundational knowledge, students will engage with advanced ML algorithms such as neural networks, k-Nearest Neighbors (kNN), logistic regression, and Support Vector Machines (SVM), as well as state-of-the-art deep learning architectures like Convolutional and Recurrent Neural Networks (CNNs and RNNs). The course emphasizes ensemble methods, optimization techniques for large-scale data, and ethical considerations in AI, including bias and interpretability. Graduate students will be required to design and implement innovative, data-driven solutions to complex, real-world business challenges, enhancing both theoretical knowledge and practical expertise in AI/ML technologies. Prerequisite: BUAN 610.
This course links a sociological understanding of social network theory and analysis with the technical skills necessary to map and analyze these social media networks through data generated by social media. The course will emphasize social network theories and concepts as it applies to social media in support of team project development and executing using the technical skills learned over the course of the semester. The course utilizes modern computing tools and network-graphs theory to analyze social networks, their organization and communication. Prerequisite: BUAN 610.
This course covers key topics such as demand forecasting, inventory management, logistics optimization, and the use of big data in the supply chain environment. Students will learn to apply statistical methods and predictive models to real-world supply chain problems, enhancing efficiency and reducing costs. Through case studies and hands-on projects, the course also emphasizes the importance of sustainability and ethical considerations in supply chain decisions, preparing students to become leaders in enhancing supply chain operations within diverse industries.
BUAN 646Project Management for Business Analytics3
This course covers the application and integration of the project management body of knowledge (PMBOK) areas to managing projects. It focuses on project management tools and techniques for defining and managing the project’s goal, scope, schedule, and budget. Other topics include project selection, project management skills, organizational structures, and risk management. Projects are used in most industries and types of organizations to achieve unique outcomes given limited time and budget. The ability to select, initiate, plan and execute projects successfully is critical to any organization’s ability to achieve its goals. Managers are often exposed to projects in different roles including but not limited to sponsors, customers, users/recipients of benefits, project managers, program managers, resource managers, product managers, and funding approvers. The ability to understand how projects are managed is an important skill for managers to succeed in their jobs. This course provides students with this knowledge and gives them the foundation to be able to start a career as project managers. At the end of this course, students should be able to create a project plan and execute it to achieve pre-defined business objectives.
BUAN 660Introduction to Blockchains, Cryptocurrencies and Smart Contracts3
This course provides an in-depth overview of blockchains, cryptocurrencies and smart contracts, as well as their uses, advantages, and limitations. Blockchain is a distributed, immutable ledger technology that is utilized to implement cryptocurrencies, smart contracts and other applications where public or semi-private visibility and verifiability are required. In addition to Blockchain architecture and use, the course will also cover the necessary computing and cryptographic background needed to understand and utilize Bitcoin and smart contracts. For both technical and business professionals, it is essential to understand these technologies, as well as their associated security issues. Prerequisite: BUAN 605.
BUAN 667Generative AI and Deep Learning for Business Analytics3
This graduate-level course focuses on the theory, implementation, and business applications of generative AI and deep learning. Topics include deep learning architectures, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs), along with the business uses of models like GPT and BERT. The course emphasizes real-world applications, including image recognition, natural language processing (NLP), and predictive modeling. Students will also explore ethical concerns surrounding AI models, including bias and transparency, and will implement projects using Python and TensorFlow. Prerequisite: BUAN 627.
This course provides students with an opportunity to apply the knowledge and skills, acquired throughout the Business Analytics program, to a comprehensive, real-world project. Working individually or in teams, students will partner with industry clients or work on faculty-suggested projects to address meaningful business problems using data analytics. Emphasis is placed on project planning, data sourcing and wrangling, analysis, and the presentation of actionable insights. Students will produce a final written report and deliver an executive-level presentation. Projects may involve predictive modeling, optimization, machine learning, business intelligence, and data visualization. Prerequisites: BUAN 610.
