In this module, you'll move from understanding metrics to displaying them. Using a sample HRIS export, you'll import data into a dashboard template, map fields to the right widgets, and learn to communicate dashboard insights using AI assistance—while ensuring your interpretations match the actual data.

Stop reacting to resignations—start predicting them. You'll learn how the talent-management cycle (attraction, development, retention) reveals where flight risk hides, and you'll practice flagging high-potential employees at risk of leaving using real workforce data in Excel. Using AI tools like ChatGPT, you'll draft defensible risk explanations that give stakeholders what they need to act. Through realistic role plays where you diagnose a colleague's missed risk signals and defend your own assessment to a skeptical VP, you'll develop the analytical skills that turn HR data into retention decisions. Designed for HR professionals, analysts, and anyone responsible for keeping top talent from walking out the door. Basic spreadsheet familiarity helpful; no HR analytics background required.

When sick-leave days spike 62% in one department, your leadership wants answers—not guesses. You'll learn why absenteeism spikes are symptoms that require systematic diagnosis, not single-cause explanations. Using fishbone diagrams in Miro, you'll classify potential causes into categories (People, Process, Policy, Environment, Tools, Management) that prevent tunnel vision and reveal hidden drivers. You'll use ChatGPT to help draft a 150-word reflection explaining why this methodology works—then verify the AI's output matches your actual analysis before sharing with stakeholders. Through realistic role plays where you diagnose a colleague's absenteeism mystery and present your findings to leadership, you'll practice the systematic problem-solving that turns HR data into actionable insights. Designed for HR professionals, people analytics practitioners, and anyone who needs to explain workforce problems without guessing. No analytics background required; access to free Miro and ChatGPT recommended.

Two candidates. One promotion. How do you decide—and defend your choice? This course teaches you to explain why performance score, tenure, and potential rating each matter for promotion decisions—and why relying on any single input leads to costly mistakes. You'll build a weighted decision matrix that makes trade-offs explicit and defensible. You'll also learn to use AI tools like ChatGPT to draft plain-language recommendations, then verify the AI's output matches your actual data. Through realistic role plays where you present to a promotion committee and coach dialogues where you navigate political pressure, you'll practice making evidence-based decisions that hold up to scrutiny. Designed for HR professionals and team leads. Basic spreadsheet familiarity helpful. Access to free ChatGPT or Claude recommended.

When your CEO asks "Is our engagement score good or bad?"—can you answer with confidence? This course teaches you to build a trustworthy engagement index that combines favorability, participation rate, and eNPS into a single picture executives can act on. You'll learn why participation rate determines whether your data is reliable, how to identify the two drivers that need the most attention, and how to document findings in stakeholder-ready language using AI assistance. Through realistic role plays where you defend your methodology to skeptical VPs and coach dialogues where you navigate competing priorities, you'll develop the evidence-based communication skills that distinguish analysts who influence decisions from those who just report numbers. Designed for HR professionals who want to move beyond survey administration to strategic workforce insight. Basic spreadsheet familiarity helpful; access to free ChatGPT or Claude recommended.

This module introduces learners to the practical integration of generative AI in people analytics workflows. Building on prior courses, it emphasizes how AI can accelerate formula creation, visualization selection, and root-cause brainstorming while requiring careful human oversight. Learners will explore effective prompting strategies, evaluate AI-generated outputs for accuracy and relevance, and document human judgment alongside machine assistance. Through videos, readings, demonstrations, and applied activities, participants will gain the skills to use AI as a supportive tool—enhancing efficiency and insight generation without compromising rigor or organizational context.

In this project, you'll apply the full range of analytics skills from Long Course 2 to assess the overall health of a fictional organization's workforce. This mirrors the real work of people analytics professionals: synthesizing multiple data sources to provide leadership with a clear picture of organizational health and actionable recommendations. The deliverable you create—a workforce health report—is the type of artifact you would present to HR leadership or include in a portfolio when interviewing for people analytics roles.