People Analytics Course Syllabus

Full curriculum breakdown — modules, lessons, estimated time, and outcomes.

Overview: This course provides a foundational understanding of people analytics, blending human resource management with data-driven decision-making. Over approximately 8 hours of content, learners will explore key applications of analytics in HR, including performance evaluation, staffing, collaboration, and talent management. The course is structured into four core modules, each focusing on a critical area of organizational people analytics, followed by a final project. Designed for beginners, the flexible format is ideal for working professionals seeking to enhance their HR and management capabilities with data insights.

Module 1: Introduction to People Analytics and Performance Evaluation

Estimated time: 2 hours

  • Understand the principles of people analytics in organizations
  • Explore challenges in measuring employee performance
  • Learn about regression to the mean and sample size considerations
  • Examine signal independence and process vs. outcome evaluations

Module 2: Staffing

Estimated time: 2 hours

  • Analyze hiring processes using data
  • Predict employee performance based on staffing metrics
  • Understand internal mobility and career development patterns
  • Learn about causality in staffing analytics

Module 3: Collaboration

Estimated time: 2 hours

  • Examine collaboration networks within organizations
  • Use data to map team interactions and communication flows
  • Evaluate collaboration effectiveness using analytical methods
  • Implement data-driven strategies to improve teamwork

Module 4: Talent Management and Future Directions

Estimated time: 2 hours

  • Apply analytics to talent assessment and development
  • Address challenges like context and interdependence
  • Understand reverse causality in talent decisions
  • Explore future trends in people analytics

Module 5: Final Project

Estimated time: 2 hours

  • Analyze a real-world HR dataset
  • Apply people analytics techniques to solve an organizational problem
  • Present data-backed recommendations for HR decision-making

Prerequisites

  • Familiarity with basic HR concepts
  • Basic understanding of data interpretation
  • No advanced statistics or programming required

What You'll Be Able to Do After

  • Apply data analytics to performance evaluations
  • Analyze staffing and attrition patterns effectively
  • Map and improve organizational collaboration networks
  • Use analytics for evidence-based talent management
  • Make informed, data-driven decisions in HR and management roles
View Full Course Review

Course AI Assistant Beta

Hi! I can help you find the perfect online course. Ask me something like “best Python course for beginners” or “compare data science courses”.