Training courses

The course covers the basic concepts of digital signal processing: analogue-to-digital conversion (ADC), digital-to-analogue conversion (DAC), spectral analysis and Fourier transform, concepts of linear systems and filtering. Basic knowledge for the design and construction of digital filters and the implementation of multirate signal processing is also provided.

You will learn how to generate discrete signals and perform their spectral analysis, create an AM signal, simulate a Gaussian data channel, simulate a QPSK modem, change the sampling rate of a digital signal, apply filters for a noisy signal.

The course is intended for learning the basics of programming in Julia, the main language of Engee. The course introduces students to the following sections: variables and data types, expressions, reading and writing data, arrays, symbols and strings, functions, conditional statements, loops, libraries.

The course is designed to learn visual modelling of analogue electrical circuits using the Engee platform.

The course is designed to introduce the basic concepts of linear algebra, such as matrices, determinants, systems of linear algebraic equations, eigenvalues and eigenvectors.

The course is designed to familiarise students with numerical methods of solving basic problems of mathematical analysis: calculating limits, derivatives, integrals, solving ordinary differential equations and their systems.

The course is designed to familiarise students with the main methods of solving nonlinear equations: graphical solution, numerical solution of nonlinear equations, solving nonlinear equations using the built-in functions "Engee", solving systems of nonlinear equations.

An introduction to technical computing in the Engee environment. Introduces the student to the Engee environment, the use of the command line and interactive scripts to perform calculations, graphing, and the basics of the Julia programming language.

You will learn the basics of physical modelling, building physical models and analysing their signals using the fundamentals of multi-domain modelling. At the end, you will consolidate your knowledge through a final project.

This course is designed to introduce the libraries and functions of symbolic maths in Engee. Each section of the course contains practical examples and assignments for self-completion.

This course is designed to introduce students to image processing in the Engee environment. By the end of the course you will learn how to use Engee to compress an image without significantly deforming the objects depicted on it.

The course is devoted to dynamic modelling of automatic control systems: linearisation of a physical system, development of a control loop with feedback using a PID controller and checking the developed controller for compliance with system requirements.

This course is designed to introduce you to the libraries and functions for solving optimisation problems in Engee. By taking this course, you will learn how to formulate optimisation problems, create variables, expressions and functions, and visualise the results of your calculations.

The course is intended for studying the capabilities of the Finite Automata library of the Engee platform.

You will learn how to graph tabular data, calculate numerical characteristics of a sample, create realisations of a normally distributed random variable, select its parameters and test statistical hypotheses about parameters and distribution type.

You will learn how to add and customise blocks, create filters for signal processing and design both discrete and continuous dynamic systems. At the end, you will consolidate your knowledge through two practical projects.