HR Analytics using MS Excel for Human Resource Management (Udemy.com)

[April 2026 update]

• Added a video on the "Analyze Data" option in MS Excel

• Added a new case study related to HR KPI's

• Added new video on how to import HR related data from PDF format reports to Excel for analysis

You're looking for a complete course on understanding HR Analytics using Excel to drive business decisions, right?

You've found the right HR Analytics using MS Excel course! HR analytics provides scientific support to decision-making concerning a firm's human resources. This course on HR analytics addresses the topic of HR analytics with a practical focus, focusing especially on demystifying analytics for Human Resource managers, from both statistical and computing point of view.

After completing this course you will be able to:

• Use MS Excel to create and automate the calculation of HR metrics and devise HR analytics techniques in your workplace

• Make HR Dashboards as per HR analytics standards and understand all the charts that you can draw in Excel

• Implement predictive ML models such as simple and multiple linear regression to predict outcomes to real-world HR problems using HR analytics techniques

• Use HR analytics tools like pivot tables filtering and sorting options in Excel to summarize and derive information out of the available HR data

• create appealing data summaries and dashboards to present the HR story in the most effective way

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this HR Analytics: Strategies & Models in Excel course.

If you are a Human Resources manager or an executive, or a student who wants to learn and apply HR analytics techniques to real-world problems of the HR business function, this course will give you a solid base for that by teaching you the most popular HR analytics models and how to implement HR analytics in MS Excel.

Why should you choose this course?

We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts through how-to examples. Each section has the following components:

• Theoretical concepts and use cases of different HR analytics models

• Step-by-step instructions on implementing HR analytics models in excel

• Downloadable Excel files containing data and solutions used in each lecture on HR analytics and Human Resource Management

• Class notes and assignments to revise and practice the concepts on HR analytics and Human Resource Management

The practical classes where we create the model for each of these strategies is something that differentiates this course from any other course available online.

What makes us qualified to teach you?

The course is taught by Abhishek (MBA - FMS Delhi, B. Tech - IIT Roorkee) and Pukhraj (MBA - IIM Ahmedabad, B. Tech - IIT Roorkee). As managers in the Global Analytics Consulting firm, we have helped businesses solve their business problem using Analytics and we have used our experience to include the practical aspects of HR analytics in this course.

We are also the creators of some of the most popular online courses - with over 600,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman - Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, HR analytics tools, human resource management, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Quizzes, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts on HR analytics and human resource management. Each section contains a practice assignment for you to practically implement your learning on HR analytics and human resource management.

What is covered in this course?

The analysis of data is not the main crux of analytics. It is the interpretation that helps provide insights after the application of analytical techniques that makes analytics such an important discipline. We have used the most popular analytics software tool which is MS Excel. This will aid the students who have no prior coding background to learn and implement HR analytics concepts to actually solve real-world HR problems.

Let me give you a brief overview of the course

• Part 1 - Introduction

  In this section, we will learn about the course structure and the meaning of some key terms associated with HR Analytics.

• Part 2 - Essential MS Excel formulas and using them to calculate HR metrics

  In this part, we will start with a tutorial on all the popular MS Excel formulas. Then we will see the implementation of these to calculate and automate the HR metrics. This is an important part of HR analytics of a human resource dataset. We also discuss a separate case study where we use Excel to calculate the average cost of external and internal hiring.

• Part 3 - Visualization in Excel and HR Dashboarding

  In this part, we will begin with a tutorial on all the popular charts and graphs that can be drawn in MS Excel. Then we will see the implementation of these to create visualize HR analytics of the available HR data. We also discuss a separate case study where we use Excel to build a department-wise demographic distribution of human resources.

• Part 4 - Data summarization using Pivot tables

  In this part, we will learn about several advanced topics in MS Excel such as Pivot tables, indirect functions, and also about data formatting. Then we will see the implementation of these to create beautiful summaries of HR analytics of the available HR data. We also discuss a separate case study where we use Excel to build a dynamic department wise demographic dashboard and format it to make it presentable.

• Part 5 - Basics of Machine Learning and Statistics