Coursera Engineering

We’ve been using GraphQL at Coursera for over three years, and we’ve learned a lot of lessons along the way. Learn what stuck & what…

This post describes our approach to upgrading our end-to-end testing system.

Three themes that have worked well for us at Coursera for data product development— from the perspective of an engineer.

This post was written by Alex Ozdemir in the fall of 2018.

Dalton is a software engineering intern on Coursera’s Growth Monetization team. He is from Toronto and studies Software Engineering at the…

This is Part I of our Causal Impact @ Coursera series.

This post will sketch out what a Webpack 3 to 4 upgrade looks like in a large modern web application.

At Coursera, millions of learners use search to discover courses. For learners with a specific intent, we need relevant results. For…

How our algorithms identify at-risk students, powering automated and human interventions

How Coursera generated course categories from thousands of courses using a data driven clustering approach.

How setting — and being reminded of — goals are moving the needle for learners

How we built a feedback loop to optimize learning nudges

How ML-powered skills insights are guiding talent strategy and development

A case study on using Coursera in the classroom

Piloting Self-Serve Analytics as a Service

In popular programming languages like Java and C#, generics serve as one of the tools for creating reusable components. By using generics…

At Coursera, we use data to power our product and better serve our learners. One example is our Skills Graph —a series of algorithms…

How targeted review material is helping close the gender gap in STEM

By Yash Kshirsagar, Austin Greene

Data solutions empowering university and industry partners, and enterprise customers

An embedded approach to in-platform analytics

A/B testing is used throughout the tech world to build more engaging and valuable products. By randomizing users into either the current…

Coursera’s algorithms guide and motivate to give learners a leg up — plus do what only machines can

ICDM 2018 Workshop on Data Mining for eLearning Personalization

By Deepkanwal Plaha

How female instructors can help close the gender gap in STEM