Certificate in Applied Talent Analytics
An organization’s success is highly dependable upon its pool of human resources and effective deployment of resources has been proven to positively drive a company’s performance. That is why human resource analytics is of paramount importance when it comes to making strategic decisions in terms of employee recruitment, engagement, retention and also prediction of employee performance across time and management of risk due to attrition.
This course is specially designed with the focus on workforce and talent analytics involving learning and development professionals. Spanning a total duration of 2 days, this course seeks to empower participants with a sound grounding in analytical concepts and frameworks, where learning is facilitated with up-to-date case studies and applications.
This 2-day workshop assumes little or minimum quantitative training though participants are expected to be comfortable with quantitative discussions and are required to sit for an open-book quiz to ensure the course objectives are met.
Who Should Attend
The Certificate in Applied Talent Analytics Program is designed for human capital development practitioners who aspire to be equipped with better decision making tools using data-driven approach and seek to understand the principles of analytics in their strategic role. Practitioners who are new to the field will gain insights of how organisations are using analytics to better understand the human capital and senior leaders in organisations will be able to validate the objective decision making for talents.
Certificate / Awards
A Certificate of Achievement will be awarded by STADA for participants who meet the minimum course requirements of passing a Quiz at the end of the course (20 Multiple Choice Questions with passing score of 70%).
Participants who fail to meet the passing criteria but have attended at least 75% of the course will be awarded a Certificate of Participation.
||Overview: Talent analytics and the role of big data analytics in the HR and L&D profession
||Introduction to knowledge management and knowledge discovery
||Principles of Analytics: Frameworks and Models
||Data Exploration and Preparation
||Analytics tools and techniques: Predictive Analytics, Segmentation Modelling, Association Mining
||Practical application: Applying principles of analytics using analytics software