Description
Embedded System Design using UML State Machines is a training course on designing and implementing event-driven systems with a UML state machine approach, published by UDEMI Academy. In this course, you will get acquainted with the principles and basics of hierarchical and simple UML mode machines step by step and you will learn valuable skills.
The ultimate goal of this course is to introduce a paradigm and approach to event-driven programming and development that uses simple, hierarchical UML machines. The training process of this course is completely project-oriented and you are expected to be able to solve the challenges in the field of latent systems with state machine techniques after the end of the course.
What you will learn in the Embedded System Design course using UML State Machines:
- Event-driven programming template
- Hierarchical state machines
- Flat state machine
- UML mode machine
- Draw a statechart
- Convert UML state charts to executable code and C and C ++
- Action object design approach
- Different design strategies and implement car modes
- State-transition table
- State-Handler approach to implementing machine scenarios
- Use of function pointers in C programming
- Graphic and graph modeling of latent event-driven systems with the UML statecharts modeler tool
- Unified Modeling Language
See Also:
Udemy – TOEFL iBT (26+) Complete Preparation Course! 2021
Udemy – Full Stack Web Development Bootcamp 2021
Udemy – NodeJS Tutorial and Projects Course 2021
Udemy – Simulation using ANSYS – Fluent English version 2021
Udemy – RF Microwave & Transmission Line Theory – RAHRF200 2021
Course specifications
Publisher: Udemi
Instructor: FastBit Embedded Brain Academy and Kiran Nayak
Language: English
Education Level: Basic to Advanced
Number of Courses: 87
Training Duration: 10 hours and 43 minutes
Course topics on 2022/2
Course Prerequisites
Basics of ‘C’ or ‘C ++’ programming
Course pictures
Installation guide
After Extract, watch with your favorite Player.
English subtitle
Quality: 720p
download link
Download Part 1 – 2 GB
Download Part 2 – 2 GB
Download Section 3 – 2 GB
Download section 4 – 423 MB
file password link
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