AI for Data Analysis & Interpretation

AI for Business Transformation Certificate 

Take a single AI course or complete all five four-week courses to earn the AI for Business Transformation Certificate. Designed for managers, working professionals, and non-technical learners, the program develops the practical skills and business judgment needed to apply AI effectively in business settings.  

Participants learn to identify appropriate uses for AI, evaluate outputs, assess organizational readiness, manage risk, improve workflows, and guide responsible adoption. The courses emphasize methods and judgment that transfer across AI tools and platforms, helping participants build skills they can apply as technologies and products change. 

Topics include AI foundations, marketing and customer experience, business operations, strategy, and AI-supported data analysis. No programming or technical background is required. Participants may take courses individually or complete the full certificate over one or more terms, depending on their schedule.  

This Course: AI for Data Analysis & Interpretation

AI for Data Analysis & Interpretation develops the analytical judgment needed to determine whether AI-assisted analysis is reliable enough to support a business decision. Rather than teaching participants simply to produce more analysis with AI, the course teaches them how to verify, challenge, explain, and defend analytical results. Participants work with realistic business data and learn how data structure, definitions, quality, and modeling choices shape the numbers managers ultimately see. 

Participants develop a disciplined approach to analytical supervision: defining the analytical problem, assessing whether the data is fit for use, constructing defensible measures, testing assumptions, and verifying results before acting on them. They learn to define data grain, identify structural and field-level risks, build repeatable transformations, and avoid common errors in aggregation and KPI construction, including misleading numerators and denominators. Excel Desktop, Power Query, and Power BI Desktop provide practical working environments for applying these methods, but the emphasis is on analytical practices and judgment that transfer across tools rather than on mastering a particular vendor platform. 

The course extends these practices into data modeling and validation. Participants build a basic Power BI star schema, examine relationships and filter behavior, create DAX measures, and reconcile results with independent calculations. AI is used as an assistant, explainer, and challenger rather than as the analytical authority. Participants remain responsible for checking assumptions, calculations, transformations, and interpretations. 

The final part of the course moves from producing analysis to supervising decisions based on it. Participants examine uncertainty and business magnitude, test how conclusions change when assumptions or conditions change, and challenge findings through sensitivity analysis and red-team review. Throughout the course, they document definitions, assumptions, verification steps, risks, and limitations so that analytical conclusions can be understood, reproduced, tested, and defended. 

For any questions about course content, please contact the course instructor, Chester King -- chking@lasell.edu. Visit https://www.linkedin.com/in/chesterhking/ for more information.

This section of AI for Data Analysis & Interpretation runs 11/11-12/11 in the Fall 2026 term. Students may enroll in the course up until 11/16.

For any questions about enrollment or Lasell Professional Studies, please contact profstudies@lasell.edu.