Automatic Data Processing, Inc. (ADP)

Data-Driven HR Analytics with AI Tools

Automatic Data Processing, Inc. (ADP)

Data-Driven HR Analytics with AI Tools

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Explain foundational HR analytics concepts and how data, metrics, and analytics support workforce decision‑making

  • Build and interpret HR analytics dashboards to identify trends, patterns, and issues relevant to business goals

  • Communicate analytics insights through clear, audience‑appropriate data stories and visualizations

  • Apply AI responsibly across the HR analytics lifecycle by evaluating outputs for accuracy, bias, and PII risk

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Recently updated!

July 2026

Assessments

9 assignments¹

AI Graded see disclaimer
Taught in English

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There are 4 modules in this course

This module introduces the foundations of HR analytics, including the differences between data, metrics, and analytics, and why clearly defined goals and success metrics matter. Learners explore common HR metrics and best practices for capturing and preparing data for analysis. The module also introduces safe data practices, including privacy and PII considerations, and shows where AI can assist with early‑stage data preparation tasks while reinforcing the importance of human oversight.

What's included

5 videos10 readings1 assignment1 discussion prompt2 plugins

In this module, learners focus on turning prepared data into meaningful insights through dashboards and analysis. Topics include designing effective HR analytics dashboards, analyzing data at both macro and micro levels, and asking the right investigative questions. Learners also examine how AI can assist with dashboard personalization, trend interpretation, and summarizing employee feedback, while practicing how to validate AI‑generated insights and avoid over‑reliance.

What's included

3 videos6 readings2 assignments2 plugins

This module explores how to transform analytics insights into compelling stories that resonate with different audiences and drive action. Learners examine the principles of data storytelling, visual design considerations, and common pitfalls in analytics presentations. The module also covers how to craft effective calls to action and apply ethical and bias‑aware language. Throughout, learners practice using AI to draft narratives and recommendations, then refine them using human judgment.

What's included

7 videos8 readings2 assignments7 plugins

The final module focuses on turning insights and calls to action into real‑world impact. Learners explore how to create implementation plans, define success metrics, and monitor results over time. The module highlights how AI can support ongoing performance summaries and trend detection, while emphasizing validation, human override, and escalation criteria. By the end, learners understand how to track outcomes, communicate results, and continuously improve analytics initiatives.

What's included

3 videos4 readings4 assignments

Instructor

ADP Learning Academy
Automatic Data Processing, Inc. (ADP)
16 Courses94,145 learners

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.