IIRF Online > Business > Human Resources > HR Analytics > People Analytics 101 : HR Analytics Fundamentals
People Analytics 101 : HR Analytics Fundamentals by Udemy
Conceptualize the Basics of Statistical Model Building.
Course Highlights
- A Step by Step Approach to solve Business Problems in the area of People Analytics.
- Understand the concepts of Statistical model building.
- Journey of Analytics.
- HR analytics and its importance.
- Employee life cycle the areas where you can use analytics.
- Get an understanding of HR metrics and the Journey from Metrics to Analytics.
- Identify a business problem and its importance. You’ll also learn how to convert a business problem into statistical problem.
- Understand the science behind gathering the data from various sources and how to do it right.
- Understand how to create an efficient data dictionary for better understanding and future reference.
- Identify the dependent and independent variable in your dataset.
- Understand and learn about various file formats in which the data is stored Understand the steps involved in data preparation.
- Various methods to measure Central Tendency, Variability and Shape of data.
- Understand the steps involved in hypothesis testing, Univariate and Bi-variate Analysis.
- Learn the concepts of Feature Engineering.
- R and Rstudio: Installation, importing files and installation of packages.
- Understand the concept of Machine Learning – Supervised and Unsupervised Learning Techniques.
Skills you will learn!
Curriculum
1 Topic
Introduction
4 Topics
Journey of Analytics
What is Analytics and Why it is important?
Analytics Maturity Model
Extras
1 Topic
Anatomy of Statistical Modeling
2 Topics
Understanding Business Problem
Knowledge Check (Business Problem Understanding)
3 Topics
Introduction
1. Employee Turnover
The Business Problem
1 Topic
Installation of R & R Studio
8 Topics
Full code
Introduction to Data Discovery & Collection
HR Data Architecture
Data list preparation and identification of Data Sources
Collect initial Data
Define Variables and create Data Dictionary
Data Verification
Knowledge Check (Data Collection)
3 Topics
Resources
Defining Variables and Data Dictionary
Data Verification
10 Topics
Introduction to Data Preparation
Uni-Variate Analysis
Missing value treatment
Outlier Detection & Treatment
Feature Engineering - Variable Creation
Feature Engineering - Variable Transformation
Feature Engineering - Dimension Reduction
Hypothesis Testing and Bi-Variate Analysis
Data Split
Knowledge Check (Data Preparation)
8 Topics
Univariate Analysis
Feature Engineering Part - 1
Bi-Variate Analysis Part - 1 (Categorical- Categorical)
Bi-Variate Analysis Part - 2 (C-C Hypothesis Testing)
Bi-Variate Analysis Part - 3 (Numerical - Categorical)
Bi-Variate Analysis Part - 4 (Numerical - Categorical Hypothesis Testing)
Feature Engineering Part - 2 (Dummy Variable Creation)
Data Split
2 Topics
Model Selection & Building
Knowledge Check (Model Selection)
2 Topics
Random Forest Theory and Code
Understanding GINI Impurity
4 Topics
Introduction to Model Evaluation
Regression Model Evaluation
Classification Model Evaluation
Knowledge Check (Model Evaluation)
1 Topic
Random Forest Model Evaluation
1 Topic
Conclusion
4 Topics
Information Regrading Bonus Lecture
1. Tools for Analytics
2. Areas of Business Analytics
Knowledge Check (Journey of Analytics)
4 Topics
3. What is Human Resources and its Importance
4. Key objectives of HR Analytics
5. People Analytics applied to Employee Life Cycle
6. Critical Areas of People Analytics
6 Topics
7. Introduction to HR Metrics
8. Ecosystem of HR Metrics
9. Metrics in critical areas of HR
10. Align HR Metrics with overall organizational strategies
11. The Journey from Metrics to Analytics
Knowledge Check (HR Metrics)
1 Topic
Final Test
1 Topic
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