What You'll Learn
This live online program helps professionals move from traditional business intelligence to practical, agentic AI. Across eight hands-on sessions, participants work with AI workflows to wrangle data, generate charts and reports, solve optimization problems, automate business processes, and build AI agents connected to databases and documents.
The course covers the full stack from ad-hoc analysis to production-ready AI systems including APIs, databases, reporting pipelines, and document AI. It also addresses prompt injection, data exfiltration risks, reliability, compliance, and governance. Participants receive cloud access to Claude Code and Python via the AI Lab—no setup required.
From Business Intelligence to Artificial Intelligence
This practical online course helps professionals understand how agentic AI can transform business intelligence, analytics, finance, operations, and reporting workflows.
Participants learn how to use AI agents to analyze data, generate insights, automate reports, connect to business systems, and build practical AI workflows that support better decision-making.
Who Should Enroll
- Executives and managers responsible for data decisions
- Finance, operations, and strategy professionals
- Business analysts and BI teams exploring AI transformation
- IT leaders evaluating AI deployment
You Will Be Able To
- Analyze data and produce reports using AI agents, even with no prior coding experience.
- Connect AI to corporate databases so that anyone can query them in plain English.
- Build automated reporting pipelines from database to finished slide deck.
- Evaluate reliability, compliance, and governance requirements for enterprise AI.
- Deploy document-based AI that answers questions from company policies and contracts with citations.
Meet Your Rice Professor
Kerry Back is the J. Howard Creekmore Professor of Finance and Professor of Economics at Rice Business and a Professor of Economics in Rice's School of Social Sciences. He teaches fundamentals of finance and quantitative finance to students in Rice's Master of Data Science program and machine learning in finance and quantitative investment strategies to MBA students. He is a former editor of the Review of Financial Studies and Finance & Stochastics, and he has authored two textbooks and numerous articles in leading finance and economics journals.
Contact
Have questions? Please e-mail kelcie.wold@rice.edu.