Databricks was born from academic research and today we are giving back to the academic community with the Databricks Academic Partners program. This program will provide academic instructors and researchers with free access to the Databricks platform for teaching and research. In collaboration with Amazon’s AWS in Education grants program, academics can also apply for grants to cover their AWS costs associated with using Databricks.
Academic instructors can use Databricks to introduce students in small or very large classes to Apache Spark by simply providing students with access credentials. Within minutes, the students will be using the Databricks collaborative notebook environment to create Spark applications. Teaching assistants can quickly deploy course-specific libraries, manage clusters, and set up access controls to enable students to work collaboratively. Course staff can also remotely work with students to help them debug their work. Databricks was recently used for two edX courses (CS 100.1x and CS 190.1x) with a combined enrollment of over 120,000 students. Instructors from University of California San Diego, University of California Los Angeles, Universidad Rey Juan Carlos (Madrid), University of California-Berkeley, and Stanford University are already using or developing courses using Databricks in the classroom.
Using Databricks, academic researchers can accelerate the research process by easily launching and managing Spark clusters, and interactively developing applications for manipulating, exploring and visualizing their data. Databricks supports easy integration with existing research project development infrastructure via GitHub integration. Students can focus on their research instead of managing a complex software execution environment. Researchers from University of California San Diego, University of California Los Angeles, University of California Berkeley, Stanford University, Howard Hughes Medical Institute Janelia Research Campus, and Lawrence Berkeley National Labs/University of California Berkeley Extension are already using Databricks to build, maintain, and deploy a wide variety of large-scale research applications. For example, machine learning researchers at UCLA are using SparkR notebooks in Databricks to develop communication-efficient ‘local learning’ methods that directly target massive and diverse datasets.
Academics interested in applying for the program can submit an application here.
