Data products facilitate meeting an end goal through the use of data. At Coursera, we’ve built data products whose missions range from facilitating better content discovery to scaling learner interventions to benchmarking learners’ performance of various skills. Each data product is a collaboration among product leaders, business leaders, data scientists, and engineers. Effective data products need effective collaborations between data scientists and engineers.

What are the factors that go into an effective collaboration? While we don’t claim to have all the answers, this post explains three themes that have worked well for us at Coursera — all from the perspective…

This post will sketch out what a Webpack 3 to 4 upgrade looks like in a large modern web application. We hope this is either an entertaining recollection or helpful for your own future upgrades.

Why upgrade?

Coursera has used Webpack in production for a few years now. Recently, we’ve been thinking about how to do code splitting more effectively in an effort to adhere to a performance budget.

As we were on Webpack 3, this resulted in an uncomfortable situation: CommonsChunkPlugin, the mechanism for ensuring that code common to many split points is extracted to a common file, is not part…

At Coursera, millions of learners use search to discover courses. For learners with a specific intent, we need relevant results. For learners with less concrete goals, we need to give a feeling of serendipity by injecting novelty and diversity into the results. In this blog post, we detail how our new search system, powered by Algolia, allows us to iterate toward this future.

Previous Search System

Search at Coursera has undergone two major revamps. Our initial approach was to return all the course data and search on the frontend. This approach became untenable as our catalog grew to hundreds of courses. We then…

From hand-coded to an algorithmic approach

Courses on Coursera cover topics ranging from photography to probabilistic graphical models to constitutional struggles in the Muslim world. This diversity makes them hard to categorize. A couple of years ago we overhauled our course categories and implemented a new categorization system we call domains and subdomains. This post covers how we defined and implemented that new system.

The Previous Course Categories

Coursera’s original categorization scheme dated back to our founding in 2012, and was heavily influenced by the content available at the time. For example, we had five categories of computer science subfields, but only one category for all of the humanities. The…

Chris Liu

Passionate about education and solving hard problems in a collaborative fashion.

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