Session:Getting to know Julia
|Description||This workshop is for everyone who wants to get an idea and some first look at the programming language Julia, which was originally designed for data analysis or scientific computing|
|Tags||julia, programming, beginner, workshop, hands-on|
|Language||de - German, en - English |
de - German, en - English
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|Starts at||2019/12/30 11:00|
|Ends at||2019/12/30 13:00|
|Location||Room:Seminar room 14-15|
In this introductory workshop you are invited to get a first look at the programming language Julia. Julia is comparatively recent (version 1.0 got released August last year) and was originally designed from scratch to provide a high-level language, which is also fast. As a result applications include scientific simulations, data science, machine learning and generally high-performance computing. Writing Julia feels a lot like writing a scripting language, but since code is automatically (and painlessly) compiled down to machine code before execution, a performance comparable to low-level languages like C or FORTRAN can be achieved.
We will use examples and a few exercises to discuss the main concepts of Julia. The main purpose is to get you curious and give you an overview. Care is taken to provide rich lists of links with further information to continue to explore Julia on your own (if you wish to do so ...).
Required previous knowledge
Prior experience with a language like C, C++, FORTRAN, python, MATLAB or similar is assumed.
I'm a chemist working in an applied math department on implementing novel algorithms in quantum chemistry. We use Julia in our current project , because we believe it's the best language for bridging different scientific communities and jointly write code . That's also what makes me enthusiastic about Julia, something I'd like to share at CCC.
If you want to try Julia during the session, best you follow the Installation instructions beforehand to get your machine set up.
- This workshop is based on a one-day introductory course, which has a similar purpose, but is a lot more detailed.
- github repository (with the Jupyter notebooks used for the course)
(I wrote the abstract in English, but I'm ok with doing it in German ... depends on who wants to participate)