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 trainings in Dehiwala- Mount Lavinia can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Dehiwala
No 154, Hotel Road, Dehiwala- Mount Lavinia, sri lanka, 10370
The Centre located in the coastal town of Mount Lavinia, which is just 12 kilometres south of central Colombo and 54 kilometres from the Bandaranaike International Airport and 4-minute walk from the Mount Lavinia railway station, and 4 km from the National Zoological Gardens of Sri Lanka. Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
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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