• Trity Course Scilab IoT

    Scilab for the Internet of Things

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  • Trity Course RPi IoT

    Raspberry Pi for the Internet of Things (with Pi-3)

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  • Trity Course Scilab AI

    Artificial Intelligence with Scilab

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  • Trity Course Scilab NCV

    Numerical Computation and Visualization with Scilab

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  • Trity Course Scilab IP

    Scilab for Image Processing and Computer Vision

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  • Trity Course Scilab BDA

    Big Data Training Series : Practical Guide to Big Data Analytics with Pig Latin, Hive and Scilab

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  • Trity Course Scilab DM

    Scilab for Data Mining

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  • Python Deep Learning

    Python for Machine and Deep Learning

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Scilab Courses

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Scilab is an open source, cross-platform numerical computational package and a high-level, numerically oriented programming language. It can be used for signal and image processing, statistical analysis, Internet of Things, data mining, etc. In Trity Technologies we have developed more than 20 courses based on Scilab since last few years.

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Raspberry Pi Courses

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The Raspberry Pi is a series of credit card–sized single-board computers developed in the United Kingdom by the Raspberry Pi Foundation with the intent to promote the teaching of basic computer science in schools and developing countries. Our very first Raspberry Pi Training is the aplication in IoT, and we are extending the training into other fields from time to time. 

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E4Coder - Automatic Code Generation

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E4Coder is a set of tools that can be used to simulate control algorithms and to generate code for embedded microcontrollers running with or without a realtime operating system. Our course focus on using the block diagram for algorithms development and the codes would be automatically generated and downloaded into the embedded boards such as Arduino Uno. A mobile robot application would be used for the training for practical hands-on. 

More about CG Courses

Numerical Computation and Visualization with Scilab



Explore How A Free Open Source Could Help In Computation and Visualization

Open source software become more and more important and famous in recent years. Explore how the Scilab could change our way of working to increase our productivity.

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“Scilab, the Open source software for numerical computation and Visualization.”


Course Synopsis


Scilab is a scientific software package for numerical computations providing a powerful open computing environment for engineering and scientific applications. Scilab is free software. It is currently used in educational and industrial environments around the world. Scilab is the responsibility of the Scilab Consortium, launched in May 2003.

Scilab includes hundreds of mathematical functions with the possibility to add interactively programs from various languages (FORTRAN, C, C++, JAVA…). It has sophisticated data structures (including lists, polynomials, rational functions, linear systems…), an interpreter and a high level programming language.


Course Objectives

This is a 2 full-days introduction course to provide the participants with a platform to learn Scilab quickly and successfully. Therefore, the participants equipped with the knowledge of Scilab to address and solve real engineering & science issues, similar to the commercial software MATLAB


Who Must Attend

Researchers, Lecturers, Scientists, Engineers and Managers that are not familiar but yet interested in using Scilab for their teaching and R&D work. This hands-on course with case studies is designed mainly for beginners and MATLAB users who are interested in learning a technical computing software that is similar to MATLAB.


No background required. Preferably with experience in basic computer operations


Course Outline

Getting Started with Scilab

  • What is Scilab and its benefits
  • Starting Scilab Interface
  • Scilab Work Directory
  • Important Menus within Scilab
  • Getting and Using Help

Basic Operations and Input/Output with Scilab

  • Expressions in Scilab
  • General Objects in Scilab
  • Input / Output in Scilab environment
  • Variable Handling and Management
  • Command History & General Commands
  • Case Study

Creating and Working with Arrays

  • Creating and Manipulating Vector and Matrix
  • Accessing and Addressing Matrix
  • Mathematical Operations with Matrix
  • Predefined Functions for Analyzing Matrix
  • Logical Operators in Scilab Case Study

Basic Programming

  • The SciPad Editor
  • Creating Script File (*.sce)
  • Creating Function File (*.sci)
  • Comparison between Script Files and Function Files
  • Online / Inline Function
  • Handling Strings in Programming
  • Scilab Program Generation Case Study

Plotting and Visualization

  • 2-D Plotting
  • Labeling and Annotating Graphs
  • Types of 2-D Plots
  • Function Plotting
  • Surface Plot (3-D)
  • Scilab Demonstrations
  • Case Study


  • Other capabilities of Scilab
  • Area of applications for Scilab
  • More documentation and online help
  • Installing Scilab in your home PC
  • Summary & Conclusions

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