[Free] Ai Data Analysis With Chatgpt And Excel
Turn messy business data into structured analysis, clear visualizations, defensible insights, and better decisions
What you’ll learn
- – Build a practical AI Data Analysis strategy connected to meaningful business outcomes.
- – Diagnose workflows, evidence gaps, assumptions, risks, and decision bottlenecks.
- – Use AI for research, analysis, generation, and coordination without delegating accountability.
- – Apply human review, verification, privacy, and quality controls at the right moments.
- – Measure efficiency, quality, user response, business value, and organizational learning.
- – Develop a ninety-day roadmap for implementation, governance, and responsible scale.
Requirements
- – No coding experience is required unless a lecture explicitly demonstrates a technical workflow.
- – Access to relevant AI tools is helpful but not required to understand the frameworks.
- – Bring a real business, client, team, project, or professional objective for the exercises.
- – Be willing to test assumptions and verify AI-generated claims.
Description
This course contains the use of artificial intelligence.
Artificial intelligence creates value when it improves a real decision, workflow, or customer outcome. AI Data Analysis with ChatGPT and Excel provides a structured system for professionals who want to move from raw spreadsheets to decision-ready insight using a repeatable, verification-first analysis workflow.
This course is designed for business analysts, managers, marketers, consultants, entrepreneurs, and professionals who work with Excel data. It moves beyond disconnected prompts and tool demonstrations. Students learn how to define outcomes, organize evidence, design practical workflows, evaluate quality, preserve human accountability, and connect AI activity to measurable results.
Across five substantial lectures, Dr. Law Payne explains the strategic logic and practical execution of AI Data Analysis. Every lecture includes a decision framework, a continuing business case, quality controls, implementation guidance, and an assignment that learners can apply to an organization, client, career, or business.
The course emphasizes responsible practice. Students learn where AI can accelerate research, analysis, generation, and coordination, as well as where privacy, bias, accuracy, security, or reputation require stronger safeguards. The aim is not maximum automation. The aim is better performance with visible ownership.
Dr. Law Payne is a business educator, growth strategist, nine-figure entrepreneur, published author, and Doctor of Business Administration specializing in Organizational Leadership and Development. His experience includes more than one billion dollars in managed sales and more than fifteen years of teaching, coaching, and mentoring across business, psychology, leadership, fitness, and education.
By the end of the course, students will have a working AI Data Analysis operating system and a ninety-day plan for disciplined implementation.
Author(s): Dr. Law Payne
