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DTSTAMP:20260707T114919Z
UID:7bbd3010-0610-47f7-8beb-33cb44f9207b
DTSTART:20200426T220000Z
DTEND:20200523T220000Z
DESCRIPTION:Speed up Python programs using optimisation and parallelisation
  techniques\n\nThe Python programming language is popular in scientific co
 mputing because of the benefits it offers for fast code development. The p
 erformance of pure Python programs is often suboptimal\, but there are way
 s to make them faster and more efficient.\n\nTopics\n\nOn this course\, yo
 u’ll find out how to identify performance bottlenecks\, perform numerica
 l computations efficiently\, and extend Python with compiled code. You’l
 l learn various ways to optimise and parallelise Python programs\, particu
 larly in the context of scientific and high performance computing.\n\n\n	P
 erformance challenges of Python programming language\n	Performance analysi
 s of Python programs\n	Efficient numerical calculations with NumPy\n	Using
  compiled code with Python\n	Interfacing Python to libraries written in ot
 her programming languages\n	Parallel programming with Python\n\n\n \n\nFo
 r further information and registration please visit FutureLearn: Python i
 n High Performance Computing.\nhttps://events.prace-ri.eu/event/1019/
SUMMARY:[MOOC] Python in High Performance Computing @ CSC
URL;VALUE=URI:https://events.prace-ri.eu/event/1019/
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