This course is designed for experienced finance professionals and has a strong focus on application of finance data and insights to improve business performance. The webinar will discuss fundamentals of predictive analytics, regression models, fundamentals of AI (Artificial Intelligence) and ML (Machine Learning), key characteristics of ML models, supervised and unsupervised ML algorithms, ensemble models and generative AI (ChatGPT/Gemini) and RAG models. The course will review a number of real-world case studies to help members explore how organizations use advanced analytics to achieve various business goals.

This course Association for Finance Professionals will offer members practical knowledge and hands-on experience in using descriptive analytics to enhance data-driven decision-making. Participants will learn how financial data analytics can be applied to various business domains. The webinar will discuss types of financial data analytics, the basics of exploratory data analytics, data profiling with central tendency and variation techniques, associative descriptive analytics, and correlation techniques. The class will include multiple case study analyses of companies effectively using descriptive analytics to advance strategic objectives.

The Special Guest Presentation at the FEDA Executive Leadership Conference featured Kevin Warsh, monetary policy expert and Shepard Family distinguished visiting fellow in economics for the Hoover Institution. Warsh reflected on his work to help guide the United States out of the 2008 financial crisis and covered the lessons from that period that can be applied to the permacrises facing businesses today. As a former member of the Fed Board, he provided an analysis of the Fed’s current policies, particularly regarding inflation, and explained how the board’s actions are impacting businesses. Finally, he decoded what business leaders can expect in both the short and long term and laid out a roadmap for how companies can spur economic growth and foster stability amid turbulent financial markets.