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The Caltech-JPL Summer School on Big Data Analytics

California Institute of Technology via Coursera

students interested
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.

Taught by

Amy Braverman, Daniel Crichton, Scott Davidoff, S. Djorgovski, Ciro Donalek, Richard Doyle, Thomas Fuchs, Matthew Graham, Ashish Mahabal, Chris Mattmann and David Thompson
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What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
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To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

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