This article lists the eleven best HR analytics courses in the world today.
Getting started with HR analytics – also called People Analytics – is a big step for a lot of people and organizations. Common questions are: Where should I start? What tools do I need? What are common traps I should avoid? An HR analytics course that answers these questions can be invaluable. In this article, I share my experience and learnings with you going through these courses.
Courses range from top-level analytics knowledge, to actually doing analytics, basic statistical knowledge, HR data and metrics, and more. Because HR analytics as a topic attracts a diverse crowd, it might mean that not every course is equally interesting for everyone. So if you feel like you are already proficient in one course’s subject, the next might be more relevant to you.
HR analytics course #1: HR Analytics Leader – AIHR Academy
Let’s be honest, this course is by far our favorite, and it may have to do with the fact that we created it! Designed as an “all-in-one” course for HR analytics managers, it is by far the most comprehensive course out there.
It prepares you to successfully lead an HR analytics function in your company. It does so by teaching you how other companies are succeeding at people analytics, and by teaching you the key ingredients you need to implement analytics successfully.
The course includes (among other things) over 30 video lessons, numerous quizzes, assignments, interviews with industry experts, and much more – all of which you can find in the course’s syllabus.
Upon completion of the course, you’ll receive a certificate from the AIHR Academy, the largest and most specialized institution in the field of online HR analytics courses in the world.
#2: People analytics – University of Pennsylvania
The second HR analytics course is the online course of the University of Pennsylvania (U.S.) on people analytics. The course is taught by three professors and introduces you to the major areas of people analytics, including performance evaluation, staffing, collaboration, and talent management. All subjects are illustrated by many real-life examples of HR analytics.
Additionally, the course provides an introduction to data management, commonly available data sources within organizations, different statistical techniques to analyze data, and common pitfalls in starting with people analytics.
The course takes around eight hours of study in total and you can do it for free. For a small price, you will have access to quizzes and a certificate of completion by the University. These quizzes are quite tough and they require you to pay close attention to the video lectures!
The biggest difference between #1 and #2 is the approach. The first course focusses on practitioners who will participate in or manage HR analytics projects. This course provides more of a high-level overview of HR analytics and some of its basics.
Start the course here.
#3: HR Analyst Course – AIHR Academy
Our number three is the most hands-on of the people analytics courses listed here. This course aims for the HR professional who wants to get started with data.
The course focuses on doing analytics using Excel and PowerBI. You will learn to:
- Leverage strategic workforce planning to make better decisions
- Calculate the Return of Investment (ROI) of HR interventions and selection methods
- Connect different data sets
- Clean and structure data
- Create interactive HR dashboards in Excel and PowerBI (see below)
- and much, much more
All of this is offered in more than 25 lessons divided into 8 modules. Knowledge is tested using quizzes, assignments and applied exercises. Want to know more? Check the course’s syllabus.
At the end of the course, you will have learned how to create an interactive dashboard that combines multiple separate datasets. The dashboard is included below.
#4: R Programming Fundamentals
The fourth (and fifth) of our HR analytics courses is about R. You can do HR analytics in Excel sheets. However, Excel has some major limitations. R is an open-source tool for statistics, visualization and data modeling. The programming language for R is specially designed to work with data and to do statistical computing. It provides statistical techniques and visualization capabilities for large data sets, as commonly used in HR analytics.
R goes further than the traditional tools that are used for HR data benchmarking and analysis, like Microsoft Excel, Access, and SPSS. R combines all of them into a programming language that can quickly import, edit and visualize data. This does mean that R requires you to do some coding, making the learning curve steeper.
R is thus also harder to master compared to Excel. However, R does offer endless computational possibilities and enables you to do much more advanced analytics compared to Excel
To get started with R, I recommend the course R Programming Fundamentals by Summer of Skills. This course teaches you the very basics of R and give you hands-on practice to get a feel of R. You can check out the course here.
#5: R Programming – John Hopkins University
John Hopkins University offers a more advanced course in R. This intermediate level course will take you roughly twenty hours to complete.
The course is taught by three professors of Johns Hopkins University. It starts off by teaches you the nuts and bolts of R, before diving into the more technical aspects of programing in R. At the end of the course, you’ll be able to run more advanced statistical techniques in R, including linear regression models.
The course is very popular, with over 400,000 students already enrolled. To enroll in this course yourself, you need to have at least basic experience in R.
To enroll, click here.
#6: Data Mining with Weka – University of Waikato
Weka is a data mining user interface. It has a visual and clickable interface which means you ‘drag and drop’ using your mouse instead of having to program as you would in R. This means that you can start this course without having to know how to program.
Weka offers both a wide array of data mining algorithms and ways to visualize data. Examples of machine learning algorithms include decision trees, Bayes, simple rules, clustering, and meta-classifiers. This course will explain all of these algorithms and their statistical backgrounds. This will help you understand the workings of data mining in general and how it can be applied to different sets of (people) data.
Weka is free software, and the sympathetic professor Ian Witten from the University of Waikato (NZ) explains in a series of practical videos how it works. Within half an hour into this course, you will run your first data mining algorithms and you created your first decision tree. The introduction of every video is played by the musical ensemble of instructing professor Witten.
This course is especially interesting for people who will not analyze data in their daily job but do want to get a grasp of the different techniques out there. Because of its user-friendly interface, Weka enables you to do a lot of different analyses in a short time-span. This helps you familiarize yourself with them quickly.
You can register for this free course here. On this page, you can also find more information about the more advanced follow-up courses. These are More Data Mining with Weka and Advanced Data Mining with Weka. The old lectures for both courses can also be freely accessed online at the Weka YouTube channel.
#7: Basic statistics – University of Amsterdam
In R, you learn how to use statistics to run algorithms. However, doing statistics without really understanding it, poses a risk. So whenever we talk about HR analytics courses, a statistics course needs to be included. In the end, data science is all about statistics so it is hard to fully grasp the possibilities and pitfalls of HR analytics without a solid understanding of statistics.
The Basic Statistics course from the University of Amsterdam is taught by professors Matthijs Rooduijn and Emiel van Loon. The course explores basic statistical concepts such as correlation, regression, normal distributions, probabilities, sampling, confidence intervals, and different types of statistical errors. All these concepts apply to data science and form a required foundation for anyone looking to start with any form of analytics.
The course requires roughly ten hours of study in total. Basic Statistics is part of a five modules specialization called Methods and Statistics in Social Sciences, which dives even deeper into quantitative research methods. The other courses in this specialization are relevant for people analytics as well.
#8: The Analytics Edge – MIT
Data analysts are in high demand. The Massachusetts Institute of Technology (MIT) offers a deep-dive into data analysis. This is the expert level course that you can follow if you have a good understanding of both statistics and R.
The program dives into the different techniques of data analysis, much like the Data Mining with Weka course. The course uses R as a programming language. Compared to Weka, R has a steeper learning curve but offers more possibilities for data structuring, analysis, and visualizations.
Taught techniques include regression analysis, decision trees, linear optimization, clustering, and data visualization. 9 different professors and Ph.D. students worked on this program, including Dimitris Bertsimas and Allison O’Hair.
If you want to analyze large amounts of data yourself and become a data scientist, this is the course for you. You can find it here.
#9: The key principles of Human Resource Management – University of Minnesota
Another important aspect in HR analytics is… HR. This course focuses on the key principles of HRM and is taught by The Carlson School of Management at the University of Minnesota (U.S.). This course is especially relevant for people who are lacking experience in human resources management.
The Carlson School offers five courses that cover the basics of the people management process. The courses range from recruitment to hiring, onboarding, performance appraisal and compensation management.
Professor Budd teaches the courses. They include reading material, tests and it ends with an assignment. Every course takes around twelve hours. You can find more information here.
As the title suggests, this course is an introduction to the basics of people analytics. Alex Dolinsky and Ilya Breyman of the Moscow Institute of Physics and Technology (MIPT) made this course for aspiring HR professionals and managers.
The entire course takes about 10 hours to complete and is split up into 7 parts with each a separate topic, including performance management, culture, motivation and engagement, compensation, recruitment, and workforce planning. Because the course focusses on aspiring HR professionals, people with more experienced in HR will learn more by following the #2 Warton People Analytics Course.
The course includes several case studies that can be uploaded for review. These are a very practical and fun part of the course. You can follow this course here.
#11: Strategic HR Metrics – AIHR Academy
The first starting point for most companies when it comes to analytics, are HR metrics. It is hard to do analytics if your basic data is not on point. This course teaches how to create HR metrics that help you to drive the strategic goals of the business.
Becoming data-driven is sometimes much easier than you think. Tracking and communicating key performance indicators (KPIs) that help the business, is oftentimes much more effective than doing advanced analytics to solve a specific issue. On top of that, how will you, for example, predict turnover, if you don’t even know how to measure a turnover rate? This course will explain how to measure turnover, and how to identify the drivers of turnover. This helps you to measure and track these as well.
For the majority of companies, people analytics revolves around getting the basics right. Only when there is a solid data-driven basis, will people analytics add its true value. This course on HR metrics teaches you these basics.
This article started with five courses back in 2017. These were all the available courses at the time. Now there are 11 – and many more that didn’t make the cut. If there are any high-quality courses that you feel we’ve missed, please post them in the comment section below. I would be happy to add these HR analytics courses to this list!