Corporate learning at scale: Lessons from a large online course at Google

Arthur Asuncion, Jac De Haan, Mehryar Mohri, Kayur Patel, Afshin Rostamizadeh, Umar Syed, Lauren Wong

Research output: Contribution to conferencePaperpeer-review


Google Research recently tested a massive online class model for an internal engineering education program, with machine learning as the topic, that blended theoretical concepts and Google-specific software tool tutorials. The goal of this training was to foster engineering capacity to leverage machine learning tools in future products. The course was delivered both synchronously and asynchronously, and students had the choice between studying independently or participating with a group. Since all students are company employees, unlike most publicly offered MOOCs we can continue to measure the students' behavioral change long after the course is complete. This paper describes the course, outlines the available data set and presents directions for analysis.

Original languageEnglish (US)
Number of pages2
StatePublished - 2014
Event1st ACM Conference on Learning at Scale, L@S 2014 - Atlanta, GA, United States
Duration: Mar 4 2014Mar 5 2014


Other1st ACM Conference on Learning at Scale, L@S 2014
Country/TerritoryUnited States
CityAtlanta, GA


  • Connectivist MOOCs
  • Corporate training
  • Distance learning
  • MOOCs
  • Online learning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software


Dive into the research topics of 'Corporate learning at scale: Lessons from a large online course at Google'. Together they form a unique fingerprint.

Cite this