The increasing amount of scientific data being collected through sensors or computational simulations can take advantage of new tools for being processed in order to extract new meanings out of raw data. The purpose of this course is to present mostly used Python libraries in this filed which can help processing and manipulating large amount of data sets. The course will consist of introductory lectures and hands-on sessions.
Basic principles of Python, Pandas, SciPy, Intel DAAL. Basic understandings for problem analysis and optimization. Project design and strategies for building a scalable data analysis application. About half of the course will consist of practical hands-on sessions.
Students, PhD, and researchers in computational sciences and scientific areas with different backgrounds, looking for new technologies and methods to process and analyse large amount of data.
Participants must have basic knowledge in programming with Python and using GNU/Linux-based systems. The participation to the course "Python for Computational Science" is highly recommended.