Databricks Lecture Series at UC Berkeley School of Information

This is a collaborative post from Databricks and UC Berkeley. We thank Tia Foss, Director of Philanthropy, UC Berkeley School of Information, for her contributions. Databricks began in the computer labs of the University of California, Berkeley, where talented computer science graduate students, such as Matei Zaharia and Reynold Xin, realized that open-source, cloud-based scalable […]

This is a collaborative post from Databricks and UC Berkeley. We thank Tia Foss, Director of Philanthropy, UC Berkeley School of Information, for her contributions.

Databricks began in the computer labs of the University of California, Berkeley, where talented computer science graduate students, such as Matei Zaharia and Reynold Xin, realized that open-source, cloud-based scalable data analytics would drive the future of machine learning (ML) and artificial intelligence (AI). The relationship between Databricks and UC Berkeley is ongoing and important to both entities — Databricks embraces the talent that the university produces, and UC Berkeley engages with Databricks to bring next-generation technology and ideas to students.

Lecture series continues!

This is why we are excited to announce the continuation of the Databricks Lecture Series at the UC Berkeley School of Information! Launched last year, this lecture series features thought leaders and practitioners from Databricks covering top-of-mind topics in data science, such as MLflow and Delta Lake use cases, software practices in data management and the business value of data-centric solutions. The audience is composed of graduate students and alumni of the UC Berkeley School of Information’s Master of Information and Data Science (MIDS) program, as well as a broad community of students, instructors, researchers and analysts throughout the UC Berkeley data science and computer science community. MIDS is an online program, so the audience is geographically diverse and many students are mid-career, full-time working professionals already well-versed in various aspects of data science, data engineering, analytics, ML, AI, deep learning and related disciplines.

Capstone student projects

In addition, Databricks will be sponsoring student capstone projects for the 5th Year MIDS program, an intensive Master in Data Science open to UC Berkeley undergrads to complete in a 5th year following graduation. The degree offers graduates a strong advantage in a competitive profession.

The Databricks-Berkeley partnership is critical to sharing ideas between industry and academia, building connections between students and industry, and enhancing education through capstone projects that prepare them for life beyond campus.

New teachers and students wanted!

If you are teaching analytics at scale, check out the Databricks University Alliance. This program helps students and professors learn and use public-cloud-based analytical tools in college classrooms virtually or in-person. Enroll now and join more than 200 universities across the globe that are building the data science workforce and data teams of tomorrow. If you are a professor or student interested in working with Databricks on using public data sets to drive social change, please contact [email protected] We believe that thoughtful collaboration can make a difference!

Upon acceptance, members will get access to curated content like example data science workspaces (“notebooks”), training materials, tutorials, pre-recorded content for learning data science and data engineering tools, including Apache Spark, Delta Lake and MLflow. Students focused on individual skills development can sign up for the free Databricks Community Edition and follow along with these free one-hour hands-on workshops for aspiring data scientists, as well as access free self-paced courses from Databricks Academy, the training and certification organization within Databricks.

The Databricks University Alliance is powered by leading cloud providers such as Microsoft Azure, AWS and Google Cloud. Those educators looking for high-scale computing resources for their in-person and virtual classrooms may apply for cloud computing credits.

Programs for working data scientists

If you are a working professional and want to take your data science career to the next level, be sure to look at the UC Berkeley Master of Information and Data Science program. The rigorous and holistic curriculum prepares students to become leaders in the data science field. Its multidisciplinary curriculum, experienced faculty from top data-driven companies, accomplished network of peers, and flexibility of online learning, bring the global prestige of a UC Berkeley education to students wherever they are.

Check out the Databricks-UC Berkeley lecture series and the Databricks Unversity Alliance.

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Source: Databricks