Online or onsite, instructor-led live Scilab training courses demonstrate through interactive hands-on practice the basic and advanced functions of Scilab.
Scilab 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. Onsite live Scilab training can be carried out locally on customer premises in Bratislava or in NobleProg corporate training centers in Bratislava.
NobleProg -- Your Local Training Provider
Bratislava CBC
8/A, Karadzicova, Bratislava, slovakia, 821 08
NobleProg Classroom in Bratislava is located in Regus Office at City Business Center building.
CBC can be easily reached via public transport:
- Trolleybus: 42, 60, 72
- Bus: 50, 70
heading to Autobusová stanica or:
- Trolleybus: 40
- Bus: 78
heading to Malý trh.
Google link: https://maps.app.goo.gl/Dcrw7uaxCvXYG8kQA
CBC is part of Nové Nivy - a ground breaking ecosystem born on a revitalised ‘brownfield’ site in the locality of Mlynské nivy.
Scilab is a well-developed, free, and open-source high-level language for scientific data manipulation. Used for statistics, graphics and animation, simulation, signal processing, physics, optimization, and more, its central data structure is the matrix, simplifying many types of problems compared to alternatives such as FORTRAN and C derivatives. It is compatible with languages such as C, Java, and Python, making it suitable as for use as a supplement to existing systems.
In this instructor-led training, participants will learn the advantages of Scilab compared to alternatives like Matlab, the basics of the Scilab syntax as well as some advanced functions, and interface with other widely used languages, depending on demand. The course will conclude with a brief project focusing on image processing.
By the end of this training, participants will have a grasp of the basic functions and some advanced functions of Scilab, and have the resources to continue expanding their knowledge.
Audience
Data scientists and engineers, especially with interest in image processing and facial recognition
Format of the course
Part lecture, part discussion, exercises and intensive hands-on practice, with a final project
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