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HR Analytics / People Analytics

Learn real life hands on cases

LIVE CLASS

HR Analytics / People Analytics

Beginner to Advance

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CATEGORIES

People Analytics

Machine Learning

HR Analytics

Data Analytics

Highlights

53 hours of training with certification

Build Dashboards, Perform Statistical Analysis

23 Hrs Self-paced Sessions

53 hours of training with certification

Build Dashboards, Perform Statistical Analysis

23 Hrs Self-paced Sessions

30 Hrs Live Online Sessions

30 Hrs Live Online Sessions

Learn and Implement using MS-Excel & R Language

Gain expertise with 50+ hands-on exercises

Learn and Implement using MS-Excel & R Language

Gain expertise with 50+ hands-on exercises

Syllabus

Analytics Overview
  • Introduction to Analytics
  • Three Levels of Analytics – Descriptive, Predictive, Prescriptive (Analytics Maturity Model)
  • Tools for Analytics
Duration
  • 1 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • Create awareness and excitement about Analytics and how Analytics can ease the day to day working and make analysis more accurate
Topics
  • Introduction to HR Analytics & HR Problems that are solved using Analytics
Duration
  • 1 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • Important HR decisions that can be made using Analytics
Topics
  • Important HR Metrices
Duration
  • 1 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • Introduction to some commonly used matrices to do analysis and how one is different from the other
Tools/ Technique
  • Excel
Topics
  • Anatomy of Statistical Model
Duration
  • 1 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • A step by step approach to solve any business problem
Topics
  • Understanding Business Problem
Duration
  • 0.5 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • A Guide on how to understand a business problem
Data Discovery and Collection
  • HR Data Architecture
  • Data List Preparation and Identification of Data Sources
  • Collect Initial Data
  • Define Variables and Create Data Dictionary
  • Data Verification
Duration
  • 2 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • The key actions that you need to perform in the process of discovering and collecting
Tools/ Technique
  • Excel and R
Data Preparation
  • Univariate Analysis
  • Missing Values
  • Outliers
  • Variable Creation
  • Variable Transformation
  • Dimension Reduction
  • Hypothesis Testing
  • Bivariate Analysis
  • Data Split
Duration
  • 9 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • Learn the various steps involved in preparing data before proceeding to model building
Tools/ Technique
  • Excel and R
Model Selection and Building
  • Linear Regression (Theory)
  • Logistic Regression (Theory)
  • K-means Clustering (Theory)
  • Principal Component Analysis (Theory)
  • Linear Regression (Practical)
  • Logistic Regression (Practical)
  • K-means Clustering (Practical)
  • Principal Component Analysis (Practical)
Duration
  • 8.5 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • Learn some core Machine Learning algorithms and how to Implement them
Tools/ Technique
  • Excel and R
Model Evaluation
  • Regression Model Evaluation
  • Classification Model Evaluation
Duration
  • 2 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • Learn some important metrics which help in evaluating Machine Learning algorithms
Tools/ Technique
  • Excel and R
Topics
  • Attrition Prediction
Duration
  • 4 hrs
Mode of Learning
  • Online Live Session
Objective of The Session
  • Prediction of empoyee attrition (turnover) an end to end hands on project which helps you predict which employees will resign
Tools/ Technique
  • Excel and R
Topics
  • Build Dynamic Excel Dashboard from Scratch
Duration
  • 3.5 hrs
Mode of Learning
  • Self-paced learning
Objective of The Session
  • Create Eye-Catching, Dynamic, Interactive Microsoft Excel Dashboards
Tools/ Technique
  • Excel
Topics
  • Using MS Excel (Excel Analytics)
Duration
  • 4.5 hrs
Mode of Learning
  • Self-paced Learning
Objective of The Session
  • Using MS Excel’s Data Analysis Toolpak to perform HR analytics on various business cases
Tools/ Technique
  • Excel
Topics
  • Factors Impacting Performance Appraisal
Duration
  • 4.5 hrs
Mode of Learning
  • Self-paced Learning
Objective of The Session
  • Use Linear Regression Technique to Discover Important Factors affecting Salary Hike
Tools/ Technique
  • Excel
Topics
  • Optimizing Sales through HR Analytics
Duration
  • 4.5 hrs
Mode of Learning
  • Self-paced Learning
Objective of The Session
  • Employee Segmentation using well-known technique RFM Analysis using R
Tools/ Technique
  • R
Topics
  • Predict job offer drop out using R
Duration
  • 2.5 hrs
Mode of Learning
  • Self-paced Learning
Objective of The Session
  • A hands-on project to optimize recruitment strategy by predicting candidate offer drop out using R
Tools/ Technique
  • R
Topics
  • Employee Satisfaction using R
Duration
  • 3.5 hrs
Mode of Learning
  • Self-paced learning
Objective of The Session
  • A hands-on project to identify Critical Employee Satisfaction Attributes using Factor Analysis in R
Tools/ Technique
  • R

FAQs

Simple, you can become a data scientist. Of course, it comes only with practice and perseverance. The most important outcome is that we will put you in a structured learning path wherein even after completion of course, you can keep learning and building your profile without any confusion like you are in now.

Mentorsship will include – giving access to end to end models built already for reference. Helping students to build more projects. We will have 1 or 2 group mentorship sessions every week. The outcome is build a profile for you..

No prior knowledge is required except the motivation to learn.

REVIEWS

I am already a Data Scientist and didn't know anything about how Data Science is changing HR Analytics. This course has given me great insight on the matter. I will look for more practical datasets and apply some of the techniques described here and try to practice problem solving.
- Shreya Chakrabarti -
The presenter spent a lot of time pulling the information together and the flow is easy to follow. As an experienced HRIS person, this is a good refresher. It is also suitable for someone just getting into HR Analytics and statistics.
- Greg Laney -
Great course for beginners who wants to pave their way in HR Analytics. Strongly recommend this course..... Btw it helped me land a job in HR Analytics.
- Pallavi Kaushal -
Yes, it was a good match for me because the concepts are very well explained with pertinent examples.
- Ujjal Paul -
It's a wonderful experience as I have learned a lot from this course.
- Nabarun Nandi -
Detailed description and explanation. Very helpful in understanding the complex subject.
- Jayadrita Mukherjee -
Gives an insight into the ways data can be used in the decision making process if used in the right way.
- Sudha HR -
Very good. To get an overview of people analytics, various HR matrices, statistical methods, how to approach a business problem, derive inferences. Good content and explanation for a beginner. Keep it up!
- Sarath TV -
Good and very solid beginner course in HR Analytics with brought overview of concepts, metrics and KPI and introduction to data analytics in HR with the help of anatomy of statistical model. I loved the way Hypothesis testing is explained. I have been always looking for such detailed explanation.
- Saumya Mishra -
As a person working with HR Information System, it gives an insight to what the HR data can tell of people's decisions for past, present and future...
- Patrick Jim -