The Caltech-JPL Summer School on Big Data Analytics (Coursera)

The Caltech-JPL Summer School on Big Data Analytics (Coursera)
Free Course
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Effort
Certification
Languages
The students should have a solid background in scientific computing and data analysis. Good programming skills in at least one modern computer language are needed, as well as some knowledge of statistics, and some experience with scientific data analysis.
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The Caltech-JPL Summer School on Big Data Analytics (Coursera)
This is an intensive, advanced summer school (in the sense used by scientists) in some of the methods of computational, data-intensive science. It covers a variety of topics from applied computer science and engineering, and statistics, and it requires a strong background in computing, statistics, and data-intensive research.

This is not a class as it is commonly understood; it is the set of materials from a summer school offered by Caltech and JPL, in the sense used by most scientists: an intensive period of learning of some advanced topics, not on an introductory level.

The school will cover a variety of topics, with a focus on practical computing applications in research: the skills needed for a computational ("big data") science, not computer science. The specific focus will be on applications in astrophysics, earth science (e.g., climate science) and other areas of space science, but with an emphasis on the general tools, methods, and skills that would apply across other domains as well. It is aimed at an audience of practicing researchers who already have a strong background in computation and data analysis. The lecturers include computational science and technology experts from Caltech and JPL.

Students can evaluate their own progress, but there will be no tests, exams, and no formal credit or certificates will be offered.



Free Course
The students should have a solid background in scientific computing and data analysis. Good programming skills in at least one modern computer language are needed, as well as some knowledge of statistics, and some experience with scientific data analysis.