Data Analytics for Business Professionals

Hearing the phrase “AI analytics” can sound daunting but don't fret. In this course, instructor John Johnson teaches you how to think about AI as a super tool that can make you more efficient and effective. Data analytics can help cut costs, speed up delivery, generate forecasts, and improve outcomes for your business over time.

Rather than trying to teach the complicated mathematical and statistical techniques that an AI tool may use, John focuses on the role of a business professional in assessing, interpreting, and applying their outputs in the context of complex business decisions through targeted case studies. Find out how to collect, clean, and aggregate data from different sources across your organization, and identify when data is flawed. John gives you pointers on planning and deploying an analytics strategy that fits the specific needs of your business, covering a variety of simple techniques: averages, sampling, cherry picking, forecasting, correlation, causality, and more.

Learning objectives
Learn the importance of data quality and reliability for AI analytical tools.
Recognize data pitfalls in AI analytical tools and the important role of the human analyst in assessing outputs and decision assistance.
Use real-world examples of data issues and challenges to make lessons more tangible.
Apply foundational data analytics concepts within multiple case studies to learn to assess and evaluate the reliability and AI analytical outputs.