Students will be introduced to problems in data analytics arising from both the machine learning community and the scientic computing community. The school will also include perspectives from industry, such as Hodge Star Scientific Computing, IBM, and Nvidia as well as from academic instructors. A unique strength of this school will be to expose students to “end-to-end” multidisciplinary topics, which span several traditionally disparate areas. The courses will give a background on methods and algorithms for data analytics, approximation algorithms to deal with large volumes of data, languages and tools for implementing those algorithms on large scale computers, and data-driven applications from scientific computing and machine learning.