Focuses on using information technology to support business processes. The purpose and composition of information systems, the utilization of technology and hands-on experience in developing microcomputer business applications with productivity tools (Microsoft Excel and Access).

Focuses on using information technology to support business processes. The purpose and composition of information systems, the utilization of technology and hands-on experience in developing microcomputer business applications with productivity tools (Microsoft Excel and Access). Restricted to SBA honors students.

This course will present topics related to managing information systems projects and digital business from a global perspective. Project management issues such as analyzing stakeholders, defining expectations, defining project deliverables, analyzing scope, collecting requirements, developing schedules, and mitigating risk, will be covered. Also, variety of digital business issues, such as digital business models, disruptive forces, and digital strategies will be covered from a global perspective.

This course covers basic principles in data modelling, and turning big data into intelligent actionable insights. Through the use of real business case studies and lab sessions students will develop a comprehensive, innovative and practical approach to data analytics that enables them to solve diverse and complex business problems.

This course covers basic principles in data modeling, and turning big data into intelligent actionable insights. Through the use of real business case studies and lab sessions students will develop a comprehensive, innovative and practical approach to data analytics that enables them to solve diverse and complex business problems. Requires C- or better in ISSCM 241H or ISSCM 241 or STAT 103, INFS 247 or INFS 247H, and one of the following: MATH 110, MATH 118, MATH 130, MATH 131, or MATH 161.

Covers current concepts in database theory and use. The course teaches design, implementation, and utilization of relational database management systems by covering the processes, tools, and methodologies such as business requirement collection, ER modeling, relational modeling, normalization, SQL, and MS Access.

This course studies methods for analyzing, developing and implementing business information systems. Stages of the systems development life cycle are explored in depth. Tools and techniques for structured and object-oriented analysis and design are discussed.

This course focuses on extracting insights from complex datasets and progresses from data mining and R principles to data transformation and data mining techniques. Using deep learning and large language models, it addresses challenges in AI analytics, emphasizing ensemble learning techniques, model evaluation, and the handling of big data.

The amount of data that our world generates is growing at a torrid pace. Sifting through & making sense of these humongous mountains of data is crucial to ensuring business growth, success and to making scientific discoveries & advancements. Data visualization plays an important role in this process.

This experiential and research-focused course explores the newest developments in the field of user experience (UX) & biometrics (e.g., collecting and analyzing human behavior data through eye tracking, galvanic skin response, facial expression, voice, and brain activity) and introduces various methods used in cutting-edge research laboratories to study human insight in business contexts. Theoretical UX concepts and practical skills in biometric data collection and analysis will be explored using the latest academic research and hands-on work with biometric hardware, software, and data. Students will complete and present the original human subject research project (team-based and with IRB approval) using biometric trackers and biosensors. The research project will be documented in the format of a full academic article.

This course focuses on how to effectively use the Python computer programming language to support decision making in business. We will particularly focus on using Python for manipulating and analyzing data. In addition to covering the concepts of programming, this course covers working with external data, debugging code and developing user interfaces.

This course focuses on how to effectively use Microsoft Office's built-in programming language, Visual Basic for Applications (VBA), to build models, primarily in Excel. We will cover issues that facilitate the construction of robust and readily understandable models in the VBA language. Starting with basic modeling functions, the course will progress through complex modeling skills. This course assumes that you are familiar with Basic Excel operations.

Business analytics is the practice of using methodically collected data to drive decisions about business and in business applications. The goal of the course is to introduce students to the current approaches, tools, and techniques involved in this practice. Because many topics and concepts in business analytics are best learned through hands-on work, time will be spent obtaining, processing, analyzing and visualizing data that pertain to different business cases. Students will use R, arguably the most popular analytical software used by data scientists. During this course, students will learn to use R, as well as gain and help improve business insight through data-driven analytics. Restricted to Graduate School of Business students.

This course examines the integration of statistical methods with artificial intelligence (AI) techniques to analyze and interpret complex data. Students will study key statistical concepts, including descriptive statistics, random variables, probability distributions, estimation, hypothesis testing, regression, correlation analysis, and model building. AI-driven approaches will be introduced for various topics. Emphasis is placed on using statistical software and AI to facilitate data analysis and address real-world problems effectively.

This course uses database systems as the focus for studying concepts of data modeling and data manipulation. Procedures for creating, managing, sorting, and processing data are discussed. Concepts of relational database methods are covered as well as the issues that arise in managing information in a database and using it to support business processes.

The concept of big data, distributed computing frameworks, and massively parallel processing databases are also covered. Students will become proficient using open source databases, performing extensive advanced SQL programming, writing scripts and manipulating strings, numbers, data, etc. within a database.

Data Mining involves the search for patterns in large quantities of data using techniques such as clustering, decision trees, neural networks, and association analysis. Machine learning, the process of using mathematical models of data to help a computer learn without direct instruction, an important application of artificial intelligence (AI), is also introduced.

Techniques of forecasting and model building are introduced. Methods covered are simple and multiple regression, introduction to time series components, exponential smoothing algorithms, and AIRMA models - Box Jenkins techniques. Business cases are demonstrated and solved using the computer.

Provides a core set of skills for planning, managing and executing systems analysis and design processes in e-business and Web-based environments. Topics typically include project initiation and planning, methods used in the determination of information requirements, prototyping, techniques used in systems design, testing and implementation strategies.

This course introduces the student to economic and business practices of a foreign country using the analysis of data, and on-site experiences. We will focus on business strategies, impediments, and challenges in light of the culture, politics, history and institutions of a selected country. We will interact with a variety of local people such as small business owners, firm managers, economists, journalists, and students, in order to inform our understanding and analysis.

The amount of data that our world generates is growing at a torrid pace. Sifting through & making sense of these humongous mountains of data is crucial to ensuring business growth, success and to making scientific discoveries & advancements. Data visualization plays an important role in this process.

Perhaps one of the biggest challenges facing organizations is bridging the gap between those who have technical expertise in information systems and those who are managerial decision makers. This course builds on the decision strategy course to help address that challenge.

The course covers concepts related to data organizing and database modeling, and the managerial issues related to the design, implementation, and utilization of systems that support operational data use and provide infrastructure for business data analytics. Enrollment limited to EMBA Cohort.

The course covers the effective uses and applications of data analytics; including On-Line Analytic Processing/Business Intelligence, data mining techniques and their particular applications and data visualizations methods and tools. Enrollment limited to EMBA Cohort.

This course will focus on the R language and will build on the introduction from INFS 443.

The rapid advancement in technology necessitates an equally rapid advance in the ethics of data analytics. We will explore ethical questions in this field through the use of business case studies. We will also look at examples of ethical codes of conduct.

Students will explore human perception and cognition, the use of best design practices, and interacting/storytelling with data.

This 10-week intensive course aims at mastering the end-to-end process of discovering, designing, developing, delivering, and managing products in context to data, machine learning and artificial intelligence. The course concentrates on strategic thinking and tactical implementation of data driven products and provides skills needed to become a successful product manager.

Scheduled classes are offered on an ad hoc basis. Specific titles, prerequisites and content will vary.