Databricks Sponsors Free Online Course Introducing Apache Spark
Databricks, a company founded by the creators of the popular open-source Big Data processing engine Apache Spark, is a firm that you may not have heard much from yet, but you will going forward. The company has healthy venture funding of more than $47 million, and Andreesen Horowitz is one of the investors, with Ben Horowitz on board.
Folks in the Big Data and Hadoop communities are becoming increasingly interested in Apache Spark, an open source processing engine for Hadoop data built for speed and advanced analytics. It was developed in 2009 in UC Berkeley’s AMPLab, and open sourced in 2010. Databricks had previously announced the launch of several massive open online courses (MOOCs) focused on distributed analytics using Spark. The courses are being made available now through BerkeleyX, in collaboration with the MOOC provider and online learning platform, edX. Here are details on an initial Spark course you may be interested in.
The Databricks-sponsored courses are designed to augment the company's efforts to grow the Spark community. They provide students with hands-on experience with Spark's analytics and real-time capabilities to deliver insights into data. The launch of these courses comes on the heels of a series of Apache Spark training offerings from Databricks, including the Spark Certification Program for System Integrators and the Spark Certification Program for Developers.
If you have a little programming and Python experience, you can sign up for "Introduction to Big Data with Apache Spark," a course that starts on June 1, and is available for free. Offered through BerkeleyX, in collaboration with the MOOC provider and online learning platform, edX, the course lasts five weeks and takes about five to seven hours per week. It will provide everything needed to get going using Spark for data analysis.
Cloudera is also rallying behind Spark. The company previously announced Apache Spark training "to prepare developers and software engineers to build complete, unified applications that combine batch, streaming, and interactive analytics."
And, to learn more about Spark, see our post found here.