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On December 19th, the fall 2016 datascience@berkeley graduates presented their capstone projects in a public webinar. For the capstone project, the graduates were tasked to solve a real-world situation or problem utilizing their data science skills in communication, problem-solving, influence, and management to provide a fully realized solution.

Machine learning continues to deepen its impact with new platforms that enable more efficient and accurate analysis of big data. One such platform is Apache SystemML, which allows for large-scale learning on the underlying Apache Spark platform, while maintaining the simple, modular, high-level mathematics at the core of the field. In a recent webinar, Mike Dusenberry, an engineer at the IBM Spark Technology Center presented the work he and his team are doing to create a deep learning library for SystemML and solve for performant deep learning at scale. Here, we’ll provide the key points that Mike discussed, as well as additional resources for further exploration.

On August 25, the summer 2016 datascience@berkeley graduates presented their capstone projects in a public webinar. For the capstone project, the graduates were tasked to solve a real-world situation or problem utilizing their data science skills in communication, problem-solving, influence, and management to provide a fully realized solution.

When we launched the Master of Information and Data Science (MIDS) program in January of 2014, we knew that we were taking a calculated risk. The data science field was gaining momentum, but there weren’t many established professional data science master’s degree programs in existence. This presented the I School with the opportunity to be one of the first movers in the space and, consequently, carve out a unique role in shaping the future of data science education.

On May 2, the spring 2016 datascience@berkeley graduates presented their capstone projects in a public webinar. For the capstone project, the graduates were tasked to solve a real-world situation or problem utilizing their data science skills in communication, problem-solving, influence, and management to provide a fully realized solution.

In a recent webinar hosted by datascience@berkeley, JeanCarlo “JC” Bonilla, Director of Insight and Impact at DataKind, shared his perspective on how data science can be used to not only make better decisions about the movies we watch — but also how to make our world a better place. Participants from around the world tuned in to his one-hour presentation to listen as he explored the use of data for social good.