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Introduces the fundamentals of programming, including data types and variables, to build a strong foundation. Participants will learn flow control and functions to create efficient, structured code.

Designed as an introduction to Business Analytics, which considers the extensive use of data, methods and fact-based management to support and improve decision making. Business intelligence focuses on data handling, queries and reports to generate information associated with products, services and customers, business analytics uses data and models to explain business performance and how it can be improved. The class will be built on heavy hands-on coding; it will introduce and subsequently involve extensive use of Python.

Learn how to use AI as a tool for learning, doing stats and unlocking data insights in this course. The course will also show how AI can support analysis with problem solving, probability, distributions, statistical inference, regression analysis using relevant case studies.Ìý

Helps you build your personal brand and communicate it effectively through networking and career hypothesis development. The program covers impact, foundations of a strategic job search, and creating strong résumés and cover letters.

This course exposes the students to commonly used platforms for statistical and predictive analytics. The class will go into depth of analytics using Python. Students will learn to analyze large datasets, including textual analytics such as twitter-stream analysis. The class will focus on predictive analytics.

Explores both the functional and technical environment for the creation, storage and use of the most prevalent source and type of data for business analysis, ERP and related structured data. Students will learn how to access and leverage information via SQL for analysis, aggregation to visualization, create dashboards, and be source for business intelligence.

Learn how to leverage generative artificial intelligence (GAI) to solve business problems focusing on three key aspects of GAI for business: 1) use of open and closed large language models (LLMs) for coding; 2) models that focus on text as well as multimodal models incorporating text, vision, and/or audio; 3) sharing models with stakeholders through methods and platforms including GUIs, APIs, and local/cloud hosting options. Coding experience is not a prerequisite for this course.

Equips you to communicate your professional value with confidence through networking, strategic interviewing, and digital literacy in your job search. The program focuses on impact, professional communication, and articulating your unique value proposition to stand out in competitive markets.

Market Intelligence is a marketing decision-oriented course geared toward gathering, analyzing, and interpreting data about markets and customers for both products and services. It is for managers as users of market information across marketing management, consulting, general management, and entrepreneurship to address problems of market selection, segmentation, positioning, new products, customer value and retention, pricing, communication, channel, etc.

Covers both traditional and emerging digital advertising methods, the popular platforms used to execute ads, and the leading analytic tools that can be used to assess advertising performance. Core advertising platforms covered include search, display, social media, native advertising, sponsored content and mobile. This class focuses on best practices and Key Performance Indicators that go with each advertising platform. Department consent required.

The purpose of the course is to provide students with a comprehensive introduction of the recent development in AI through the coverage of fundamental AI concepts and practical applications of these concepts in business.

Moves the student beyond structured data and sources into business scenarios where data is semi-structured to unstructured such as those from social and web applications. Specific topics include introduction to SQL-on-Hadoop, NoSQL and related distributed processing technologies. Students will learn practical application and mechanisms for getting this sort of data ready for analytics.

Provides an opportunity to execute a project for a company, integrating course work knowledge in an applied capstone experience. Allows first hand exposure to the business analytics as both an observer and creator of the business analytics process. Students work closely with an area client company to solve an important business analytics problem under the close supervision of the instructor.

Helps you build a strong foundation for lifelong career success by mastering essential skills such as salary negotiation, offer management, SMART goal setting, delivering and receiving feedback, and developing strategies for ongoing career growth.

Provides a deep understanding of how to use data on customer behavior and preferences to inform managerial decision making. Introduces methods for causal inference, modeling consumer demand, and modeling firm decisions. Applications include long-run customer management decisions (customer acquisition and retention) and short-run marketing mix (product, price, promotion and distribution) decisions. The R programming language is used for course examples and assignments. Students are assumed to have a working knowledge of R and linear regression techniques.