From People Science to Data Science analytics in HR

From People Science to Data Science analytics in HR

Public courses

£1900

- Anyone can join the training
- Course outline as presented on the website
- Small groups, 3-10 people

Private courses

Price set individually

- Training workshop just for your team
- You choose date and location of the training
- Course outline tailored to your needs

About the training

This advanced-level training course offers a solid understanding of data science applications in HR and People analytics. With this training we want to fill the gap in HR analytics and equip the HR professionalists with tools and techniques necessary to solve the most common problems in a most effective way. During the training course we show you how to run HR projects using data science framework. Practical examples guide you through the Artificial Intelligence and predictive modelling techniques required for each type of analysis. Using the software of your choice you will be able to immediately apply your new skills and insights within your organization.

Human resources is constantly evolving, used to be filled with industrial and organizational psychologists today requires more data scientists. One of the changes HR is experiencing is a move from being a people science to being data science about people.

Herbert Marrow, an HR Director at CareersBooster, recently noted: “Companies that embrace data science spend less time and money on HR management – and they do this simply by using data that has always been available but no one knew how to take advantage of it.” According to recent studies, businesses with mature people analytics perform 30% better than their competitors. The growing role of data science in HR and its potential can not be ignored at all

Who is this training for?

This course is for HR professionals who wants to be part of the data science era in HR analytics. This course is for you if you are in charge of HR analytics, especially HR Analysts, HR Managers, Data Scientists and Analysts.

What will I learn?

  • Understand the importance of people analytics using data science techniques and methods
  • Learn about the data science framework in people analytics
  • Learn about data science tools and how to apply them in HR
  • Learn about machine learning techniques to improve HR metrics and people management
  • Interpret the output from advance models and turn it into actionable insights
  • Solve HR problems with data science techniques

Course outline

  1. The new era of People Analytics
    • The people analytics advantage
    • Changes in the world of work
    • A short history of HR Analytics adoption
    • Migrating from People Science to Data Science
    • Building a peope analytics center of excellence
  2. People Analytics/HR scope
    • Identifying People/HR related questions and issues
    • Understanding People/HR data
    • Traditional HR Metrics and analytics
    • Pillars of People/HR analytics
      • Talent sourcing analytics
      • Workforce planning
      • Acquisition/Hiring
      • Engagement, Culture fit
      • Peformance, development, Lifetime value
      • Churn and Retention
      • Wellness, Safety and Health
    • Applying Data Science framework to the HR context
    • Why do we need data science in People analytics
  3. Data Science Framework
    • Defining the problem and goal
    • Collecting and managing data
    • Building the Model
    • Evaluating and validating model
    • From model output to actionable insight
    • Documenting and reporting results
    • Deployment
  4. Data Science Tools
    • Data Sources & storage
    • Data Manipulation
    • Data Visualization
    • Analytical tools & programming languages
  5. AI & Machine learning in people analytics
    • Why traditional statistical approach is not enouqh?
    • Supervised vs Unsupervised learning
    • Machine learning algorithms – classification, prediction, anomaly detection, segmentation
    • Machine learning step by step
  6. Solving HR problems with Data Science – Practical examples
    • Modelling and predicting absenteeism
    • Talent acquisition – choosing the right candidate
    • Job classification – matching employees
    • Performance management analysis
    • Employee lifetime value and cost modelling
    • Retention analytics – modeling attrition, churn analysis to protect most valuable assets

Course Curriculum

Curriculum is empty

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