Online or onsite, instructor-led live Julia (Julia Programming Language or JuliaLang) training courses demonstrate through interactive discussion and hands-on practice how to do programming with Julia.
Julia training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Ostrava onsite live Julia trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Ostrava
NobleProg Ostrava, Října 205/45, Ostrava, Czech Republic, 70200
You'll reach Platan Office thanks to the bus stop at Divadlo Loutek, just a 2-minute walk away. Leoš Janáček Airport Ostrava is located 25 km away. Platan Office have breakout area for time away from your desk or get fresh air on the rooftop terrace.
This course is oriented towards data analysts as well as research scientists. Julia is a rapidly emerging programming language with a strong focus on numerical accuracy, scientific computing and statistics. It has gained most of its reputation due to its speed of execution in conjunction with its ease of programming. What is less emphasized, although it is true, is that
Julia has a wealth of built-in and external tools for distributed and parallel computing,
it facilitates the construction of user-defined data structures,
it makes it easy to do metaprogramming, therefore to also define your ownl DSLs,
it allows interacting with several other programming languages such as C, Python and R,
it provides a multiple-dispatch programming paradigm, which in many ways helps you organize your code and makes you a better programmer and software engineer.
This course is for people that already have a background in data science and statistics. The explanations given are designed to either serve as a reminder to those that are already familiar with the concepts or inform those with a suitable background.
This course is intended for people that already have a background in data science and statistics. The explanations given are designed to either serve as a reminder to those that are already familiar with the concepts or inform those with a suitable background.
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