Methodology

The Coursera Global Skills Index assesses the skill proficiency of learners in each country, industry, and field of study, measures which skills are trending, and identifies roles that will impact the future of work.

Our Process

Central to the Global Skills Index are our Skills Graph and benchmarking methodologies. Together, they allow us to rigorously assess the skill proficiency of various countries, industries, and fields of study.

Skills Graph

The Coursera Skills Graph connects skills to content, careers, and learners through a series of machine learning algorithms.

Through it, we can understand what skills are being taught and learned on the platform.

Skills Graph

Benchmarking

Using a patent-pending algorithm, we measure skill proficiency of each country, industry, and field of study for our rankings.

Cutting Edge
Cutting Edge
for 76th percentile 
or above
Competitive
Competitive
for 51st to 75th percentile
Emerging
Emerging
for 26th to 50th percentile
Lagging
Lagging
for 25th percentile 
or below

Our Findings

We rank 60 countries, 10 industries, and 11 fields of study to understand who is proficient in critical skills spanning business, data science, and technology. These rankings provide an overview of the skills landscape around the world.

Correlations with
third-party data
Correlations with
third-party data
We correlate country and industry rankings with economic and financial data to provide insight into their associations with skill proficiencies
Trending 
<br />skills
Trending 

skills
We combine a series of on-and-off-platform metrics into a single, weighted index that provides insight into the trending skills
Top fields of study and roles
Top fields of study and roles
For a subset of the trending skills, we identify the top fields of study and occupations with above-average enrollment rates

Meet the Team

The Global Skills Index is brought to you by the Data Science team at Coursera:

Emily Glassberg Sands
VP of Data
Emily Glassberg Sands

Emily holds a Ph.D. from Harvard and leads the end-to-end data team at Coursera, where she works in machine learning, decision science, and data engineering. Her work has been featured in the New York Times, the Wall Street Journal, and National Public Radio.

Vinod Bakthavachalam
Senior Data Scientist
Vinod Bakthavachalam

Vinod is focused on forecasting skills trends using signals from the Coursera platform. He received a Master’s degree in Statistics from Stanford University. His work has been featured in the Harvard Business Review, the World Economic Forum, and the New York Times.

Rachel Reddick
Staff Data Scientist
Rachel Reddick

Rachel earned her Ph.D. in Astrophysics at Stanford, and works primarily on Coursera’s Skills Graph and related applications. Recently, she has focused on developing ways to measure learners’ skills and identify suitable roles for them based on their proficiency.

 

 

Download the full Global Skills Index

for even more data-driven insights by country, region, industry, and role.