Hong Kong Management Association

Professional Certificate in Human Resource Analytics

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Course Information

  • 27 Jun 2024 (Thu)
Registration period
9 Apr 2024 (Tue) - 26 Jun 2024 (Wed)
HKD 4,800
Study Mode
3 Month(s)
Cantonese, English
8 Hoi Wang Road Mongkok (West) KOWLOON

Course Overview

Human Resource (HR) analytics is the process of collectingand analyzing HR data in order to improve an organization’s workforce performance.

The process can also be referred to as talent analytics, people analytics, or even workforce analytics

This course is intended for HR executives who aspire to improve their data literacy through skilling-up their digital competence. It is also highly relevant to other key staff involved in the requirements input, design, development, delivery, and ultimate use of the digital initiatives including recruitment, business analysis, and operational line managers/staff.

What You’ll Learn


A) HR Talent Analytics ( 人力資源人才數據分析 )

  •  What is HR data and HR talent analytics?
  •  The major HR talent analytics applications andtheir importance
  •  Processes of HR talent data analytics

B) Understanding the people analytics ( 了解人力資源數據分析 )

  •  Understanding the HR / people data sets
  •  What are the major tools in HR / people analytics?HRM, HRIS, Python, Excel, R, PowerBI, etc.
  •  How to apply HR /people analytics tools
  •  Understanding big data in HR

C) HR Data Visualisation ( 人力資源數據可視化 )

  •  Design concept and feature of data visualisation
  •  The introduction of Apache Superset, a user-friendlydata visualisation tool that is essential to most ofthe data users today
  •  Case studies

D) HR Analytics Skills ( 人力資源分析技巧 )

  •  Definition of descriptive analytics and predictiveanalytics
  •  Applying different types of HR analysis using twomethods
  •  Using Python to demonstrate predictive analysis
  •  Case studies

E) Reporting and Decision Making from HR AnalyticsProjects ( 人力資源報告及決策分析 )

  •  Workforce analytics
  •  Data Visualisation Tools: Python, Apache Superset
  •  Decision making processes
  •  Case studies

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