📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI in Performance Management and Employee Engagement, from foundations to a certified capstone project.
Measurement
• Output, outcome and behaviour measures, and which are gameable
• Rater bias, recency effects and central tendency in review data
• Engagement surveys: construct validity, response bias and survey fatigue
Analysis
• Text analytics on review comments and open-ended feedback
• Driver analysis that separates correlation from actionable lever
• Team and manager effects, and the small-sample problem in unit-level analysis
Feedback
• Goal setting and check-in cadences supported by analytics
• Personalised development recommendations without prescriptive career tracks
• Language-model assistance in writing reviews, and the homogenisation risk
Risk
• The line between performance analytics and employee surveillance
• Transparency and consultation obligations in different jurisdictions
• Adverse impact testing where analytics informs pay or promotion
Practice
• Manager enablement and interpretation training
• Avoiding forced distribution and metric fixation
• Evaluating whether the system improved performance or only measurement
Earn government-registered certification in AI in Performance Management and Employee Engagement
e-Certificate and e-Marksheet issued on successful completion.
