The Caltech-JPL Summer School on Big Data Analytics

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.

About The Course

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.

Frequently Asked Questions

  • What resources will I need for this class?
A decent network connection and a computer that you would use for your scientific computing or data analysis.

  • What is the coolest thing I'll learn if I take this class?
How to handle big data and extract knowledge from them.

  • What background is expected for learners in this class?
See above.  By the way, it is not a class; it is an advanced summer school.

  • I don't have a strong background in computing and data analysis, or I am just curious abut these subjects.  Should I take this class?
Probably not.  You will probably get frustrated and not get much from it.  Better start with some introductory level classes in these subjects.

  • How much work is needed?
At least 4-5 hours per chapter (and there are 9 of them), if you already have a strong background in scientific data analysis and computation; and more if you don't.

  • Why are there no quizzes or exams or certificates?
Because it is not a class.  We are simply sharing with you the materials from our advanced summer school.  You can benefit from the learning, and you are the best judge of how well you have understood the material.  You may want to wait until the spring of 2015 and take a full class based on these materials.

Recommended Background

The students should have a solid background in scientific computing and data analysis.  The target audience includes upper-level undergraduate and graduate students, postdocs, or other researchers in science and technology fields.  Good programming skills in at least one modern computer language (or the ability to quickly learn one) are needed, as well as some knowledge of statistics, and some experience with scientific data analysis.  Background knowledge in computer science is a plus.