Business Analytics

An analysis of the core analytics concepts and tools for turning data into reliable information, and the ability to identify analytics types, data quality, and visualization basics.

An exploration of AI concepts, tools, and ethical implications to provide a foundation for understanding AI fundamentals, identifying practical applications, and evaluating ethical considerations.

Establishing processes for turning raw data into compelling visual narratives as well as applying design principles, choosing appropriate charts, and telling data stories.

A real-world approach for applying Machine Learning techniques for business problem-solving.  The focus will be on building and evaluating models, as well as using Machine Learning with business datasets and applications.

The development and process of frameworks for ethical, transparent, and compliant AI use, including governance strategies, mitigating AI risks, and alignment with regulations.

The process of utilizing generative AI tools to enhance creativity, productivity, and customer engagement including developing prompt engineering skills, automating creative workflows, and evaluating business processes and workflows.

Develop frameworks for managing and analyzing large-scale datasets, understanding big data systems, Business Intelligence tools, and real-time analytics.

A review of the techniques and approaches for forecasting and predictive modeling, and the ability to apply predictive models, interpret results, and support decision-making.

An integrative capstone project applying AI and analytics skills to solve a real-world problem, demonstrating work on end-to-end analytics projects, from problem definition to executive presentation.

A project-based course for developing an AI adoption plan, identifying strategic opportunities, implementing pilots, and measuring success.