Engee documentation

Training courses

Instruction for taking free online courses. The procedures for taking the courses presented in this section are advisory in nature.
1
Engee Programming Fundamentals" course
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.
 ~ 10 h
2
Course "Fundamentals of Linear Algebra"
The course is designed to introduce the basic concepts of linear algebra, such as matrices, determinants, systems of linear algebraic equations, eigenvalues and eigenvectors.
 ~ 3 h
3
The course "Mathematical Analysis"
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.
 ~ 2 h
4
The course "Solving Nonlinear Equations"
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.
 ~ 1.5 h
5
Fundamentals of Optimisation course
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.
 ~ 2.5 h
6
Symbolic Computing Course
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.
 ~ 2 h
7
Fundamentals of Statistics course
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.
 ~ 2 h

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