hi everyone, hope you’re dong well.
As far as I could catch, I suppose Julia is quiet fitted for embedded applications and implementing algorithms with high computational burden and limited available memory space . I’m looking for a roadmap for beginners to have an overview and to know what steps are needed for learning Julia alongside these purposes.
I’m already studying control engineering and familiar with MATLAB as it is widely used in the major and I know that C and Python are the most used programming languages for implementation. so, Julia, with the hindsight that provides a sort of combination of mentioned languages, seems interesting.

Purposes:
1. implementing complex (linear and non-linear) control and system identification algorithms
2. implementing AI and data-driven based algorithms
3. implementing real-time scenarios

Applications:
1. Robotics
2. auto-driven vehicles
3. Multi-agent and swarm robotics
4. Signal processing

The roadmap should contain:
1. Basic concepts of Julia
2. Courses on related packages
3. examples and real projects for training

LowLevelParticleFilters.jl contins facilities for state estimation, such as Kalman filters and other observer structures. These are used in the system identification package as well as in the JuliaSim Control package.

ControlSystemsMTK.jl is an interface package that makes it easier to solve classical control problems with ModelingToolkit models.

Control Ecosystem in Julia this page lists a number of packages that are related to control-systems and adjacent areas in Julia.

Model-predictive control We offer MPC functionality, linear, nonlinear and robust, in JuliaSim Control.

JuliaControl youtube playlist I maintain this playlist which contains a number of videos that are related to control-systems in Julia.

For examples and tutorials, we have a decent number of tutorials in the JuliaSimControl tutorial section, see the section “Tutorials” in the menu. Also see the “Exampels section” in the ControlSystems.jl documentation.