The Modern Finance Function – Transformation, Upskilling & AI in the Digital Age
1.0 CPE credits

Learning Objectives:

• Identify the key trends and drivers impacting finance teams & their transformation
• Recall the elements of a modern finance tech stack
• Identify the skillsets and upskilling needed to enable and maintain successful transformation & AI adoption

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Data Mining and Modeling
3.5 CPE credits

Learning Objectives:

• Distinguish between data mining and related terms.
• Recognize the data analytics framework’s role in a data mining project.
• Identify the goals and benefits of data mining.
• Recognize the tasks associated with building a data mining model.
• Identify the concept of clustering as a descriptive data mining technique.
• Identify the appropriate data mining techniques and algorithms for predictive analytics.
• Recognize how clustering techniques can be applied in practice.
• Recognize how regression techniques can be applied in practice.
• Recognize tools and programs that can be used for data mining and modeling.

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Charting The Future: From Tasks to Capability — Augmented by Gen AI & ChatGPT
1.0 CPE credits

Learning Objectives:

• Identify the difference between task-based Gen AI use and workflow-based capability in accounting and finance.
• Apply ChatGPT tools (Advanced Data Analysis, Deep Research, Canvas, Projects, and Custom GPTs) to create a repeatable workflow that produces an executive-ready deliverable.
• Determine the governance and validation steps required for reliable Gen AI–augmented outputs.

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Mastering Microsoft Copilot
2.0 CPE credits

Learning Objectives:

• List examples of security and privacy features found in Copilot
• Name at least three ways Copilot integrates with Microsoft 365 Apps
• Specify how to integrate your data securely into Copilot
• Differentiate between Copilot, ChatGPT, and Gemini
• Identify examples of tasks that Copilot may not be well-suited to complete

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Ethics and Critical Thinking in an AI World
3.0 CPE credits

Learning Objectives:

• Apply Kidder’s Nine Checkpoints for Ethical Decision-Making to analyze and document the steps taken in resolving AI-related ethical dilemmas.
• Determine when an AI-driven scenario presents a right-versus-wrong issue versus a right-versus-right ethical paradigm using structured ethical tests.
• Compare machine-generated audit or financial outputs with human professional review to identify discrepancies and assess reliability.
• Distinguish between ethical decision-making frameworks—ends-based, rules-based, and care-based—and select the most appropriate for a given corporate scenario.

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CFO Reporting Re-Imagined — Building Interactive Excel Reporting with Gen AI Assistance (Module 2)
1.5 CPE credits

Learning Objectives:

• Apply PivotTables, functions and formulas to create core trend, comparative, and LTM calculations.
• Use data-validation dropdowns, dependent lists, slicers, and timelines to build self-service report interfaces that guide scenario analysis and minimize input errors.
• Select lightweight automation—Worksheet_Change events, one-click VBA/Office Scripts, and refresh-all Power Query routines—to distribute ready-to-use workbooks rapidly.
• Apply Gen AI (“My Excel Buddy” custom GPT) responsibly to generate formulas, refactor macros, and assist you with all Excel related tasks.

To register, add the course to your cart and type in KRESTON at checkout.