Development of Real-Time Systems (Coursera)

Offered by EIT Digital,
Development of Real-Time Systems (Coursera)

This course is intended for the Master's student and computer engineer who likes practical programming and problem solving! After completing this course, you will have the knowledge to plan and set-up a real-time system both on paper and in practice. The course centers around the problem of achieving timing correctness in embedded systems, which means to guarantee that the system reacts within the real-time requirements.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Examples of such systems include airbags, emergency breaks, avionics, and also multi-media systems like video playback and QoS in web servers.
The course teaches how to plan real-time systems in theory using established mathematical proofs and how to implement them in practice by using the most common scheduling methods. We also learn and how to program the system in the C language using the FreeRTOS real-time kernel. Finally we have a look at the future of real-time systems namely multi-core real-time systems!
This course focus on the learn-by-doing approach with many examples and real-world programming assignments. We have 5 modules, each with a gentle graded quiz in the end and one peer reviewed programming assignment.
This course focus on the learn-by-doing approach with many examples and real-world programming assignments.
We have 5 modules, each with a gentle graded quiz in the end and one peer reviewed programming assignment.
In case you have no experience with C programming, please check you a practical course like: The Arduino Platform and C Programming
Course 3 of 4 in the Development of Secure Embedded Systems Specialization .

Syllabus

WEEK 1
Introduction to Real-Time Systems
Here is where it all starts! We will make a brave attempt to start your future career in real-time systems! This week starts by learning the basic building stones in real-time systems and the system parameters required to successfully construct a real-time system. We introduce you to the corner stone of real-time systems, namely the scheduler – and its task in real-time schedules. You learn also what kind of real-time guarantees are needed in which systems. Concretely, you will learn (1) What is needed to create a real-time system (2) Where real-time requirements are needed. (3) The task and job structure and the parameters needed to schedule a task. (4) Difference between pre-emptive and non-pre-emptive tasks. This course is also part of a Blended Master Programme in Embedded Systems.

WEEK 2
Static Scheduling
In this week we start to actually do some scheduling. We firstly have a look at the simplest type of scheduler – the clock driven scheduler. After this we deepen our learning with the fixed priority scheduler and the monotonic schedulers. We learn how the priorities are determined using these schedulers and we learn when/when not to use these schedulers. Secondly we learn how to determine if a system is overloaded in order to validate schedules without complete system simulation.Concretely, after attending this week you will be able to: (1) Schedule a set of tasks with the clock driven scheduler, with the fixed priority scheduler, with the monotonic schedulers. (2) Determine if a system is overloaded using the total-utilization method and the Urm method. (3) Program FreeRTOS to schedule a set of tasks using the fixed priority scheduler.

WEEK 3
Dynamic Scheduling
In the previous week we learned the limitations of the total-utilization method and the Urm method. We start this week off by extending these tests to tasks with short response times. The new method is also, as usual, used in practice! We then focus on improving the optimality of real-time schedules. This is done by learning the principles behind dynamic scheduling methods. Two new schedulers using the dynamic scheduling principle is learned and used in practice with a few examples; the LST scheduler and the EDF scheduler.Concretely, you will learn: (1) How to determine feasibility of a set of tasks using the time demand analysis method. (2) How to schedule a set of tasks using LST and EDF. (3) To determine when a dynamic scheduler is appropriate and when it is not appropriate.

WEEK 4
Non-Periodic Jobs
All things are easy and nice when not caring about non-periodic jobs. When including non-periodic jobs, the schedulers must take these into account to make a feasible schedule, which we learn this week. The problem is that a non-periodic job can arrive at any time, even if a periodic job is already scheduled. We learn both how to optimize a schedule for non-periodic jobs and how to validate a schedule when non-periodic jobs arrive to the schedule. Concretely, we will learn: (1) How to use the slack stealing method to optimize a schedule with non-periodic jobs (2) How to use the LRT scheduler to optimize a schedule with non-periodic jobs (3) How to use the deferrable server to optimize a schedule with non-periodic jobs (4) Formally verify a schedule with non-periodic jobs.

WEEK 5
Real-Time Operating Systems
This week is what we all have been waiting for! We will deepen our learning of FreeRTOS, its kernel and the functionalities. We demonstrate the importance of predictable computer architectures for example when determining the context switch and factors influencing this overhead. As we head towards the future, we finish this course by introducing you to multi-core real-time systems and scheduling methods for multi-core real-time systems. Concretely, you will learn: (1) The internal mechanisms of FreeRTOS, for example mutexes/semaphores and message queues. (2) Multi-core computer architectures for real-time systems. (3) Multi-core scheduling methods.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introducción a Java (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Java (Coursera)

Me llamo Elisa Viso y una de mis pasiones es la de programar y enseñar a programar. El lenguaje Java es uno de los que más me ha gustado en mis 45 años que llevo programando. Si bien te podrá parecer un poco complicado empezar a programar en Java, una vez que cubras los conceptos básicos verás qué rápido se avanza. Java, como todos los lenguajes de programación bien hechos, te dejan hacer cualquier cosa (algunas de ellas con más trabajo que en otros lenguajes y otras casi directamente de cómo piensas la solución al problema).

Nov 2nd 2026
5-12 Weeks
Programming Fundamentals (Coursera) Coursera
Duke University

Programming Fundamentals (Coursera)

Programming is an increasingly important skill, whether you aspire to a career in software development, or in other fields. This course is the first in the specialization Introduction to Programming in C, but its lessons extend to any language you might want to learn. This is because programming is fundamentally about figuring out how to solve a class of problems and writing the algorithm, a clear set of steps to solve any problem in its class.

Nov 2nd 2026
4 Weeks
Introduction to .NET Core (Coursera) Coursera
Board Infinity

Introduction to .NET Core (Coursera)

This course is an introductory-level course for software developers who want to learn the basics of developing applications with .NET Core. .NET Core is a cross-platform, open-source development platform that allows developers to create applications for Windows, Linux, and macOS. Throughout this course, students will learn the fundamental concepts of .NET Core, including its architecture, programming model, and tools. They will also learn how to create, build, and deploy applications using .NET Core.

Nov 2nd 2026
3 Weeks
Introducción a la programación en Python I: Aprendiendo a programar con Python (Coursera) Coursera
Pontificia Universidad Católica de Chile

Introducción a la programación en Python I: Aprendiendo a programar con Python (Coursera)

Decía Steve Jobs que “todo el mundo debería aprender a programar un ordenador porque esto te ayuda a pensar”. Hoy en día la programación es una herramienta fundamental para el desarrollo de la tecnología moderna. Este curso te introduce en el mundo de la programación en el lenguaje Python.

Nov 2nd 2026
5-12 Weeks
Information Theory (Coursera) Coursera
The Chinese University of Hong Kong

Information Theory (Coursera)

At the completion of this course, the student should be able to: demonstrate knowledge and understanding of the fundamentals of information theory; appreciate the notion of fundamental limits in communication systems and more generally all systems; develop deeper understanding of communication systems; apply the concepts of information theory to various disciplines in information science.

Nov 2nd 2026
13-24 Weeks
Computer Science: Algorithms, Theory, and Machines (Coursera) Coursera
Princeton University

Computer Science: Algorithms, Theory, and Machines (Coursera)

This course introduces the broader discipline of computer science to people having basic familiarity with Java programming. It covers the second half of our book Computer Science: An Interdisciplinary Approach (the first half is covered in our Coursera course Computer Science: Programming with a Purpose, to be released in the fall of 2018). Our intent is to demystify computation and to build awareness about the substantial intellectual underpinnings and rich history of the field of computer science.

Nov 2nd 2026
5-12 Weeks
Programming Reactive Systems (Scala 2 version) (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Programming Reactive Systems (Scala 2 version) (Coursera)

Reactive programming is a set of techniques for implementing scalable, resilient and responsive systems as per the Reactive Manifesto. Such systems are based on asynchronous message-passing, and their basic building-blocks are event handlers. This course teaches how to implement reactive systems in Scala and Akka by using high-level abstractions, such as actors, asynchronous computations, and reactive streams.

Nov 2nd 2026
5-12 Weeks
Solving Algorithms for Discrete Optimization (Coursera) Coursera
University of Melbourne,The Chinese University of Hong Kong

Solving Algorithms for Discrete Optimization (Coursera)

Discrete Optimization aims to make good decisions when we have many possibilities to choose from. Its applications are ubiquitous throughout our society. Its applications range from solving Sudoku puzzles to arranging seating in a wedding banquet. The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation of iron ore from the mines to the ports.

Nov 2nd 2026
4 Weeks
Introdução ao Teste de Software (Coursera) Coursera
Universidade de São Paulo, Brasil

Introdução ao Teste de Software (Coursera)

A necessidade das empresas em produzir software com qualidade tem aumentado a demanda por profissionais com conhecimentos e habilidades em Teste de Software. Entretanto, existe uma escassez de mão-de-obra especializada nesta área. Considerando essa lacuna, o curso de Introdução ao Teste de Software foi planejado para servir como um guia para pessoas que necessitam de uma fonte de consulta e/ou aprendizado na área.

Nov 2nd 2026
5-12 Weeks
Estruturas de dados Python (Coursera) Coursera
University of Michigan

Estruturas de dados Python (Coursera)

Este curso apresentará as estruturas de dados centrais da linguagem de programação Python. Vamos superar os fundamentos da programação de procedimentos e explorar como podemos usar as estruturas de dados integradas do Python, como listas, dicionários e tuplas, para realizar análises de dados cada vez mais complexas. Este curso cobrirá os capítulos 6 a 10 do livro “Python para Todos”. Este curso aborda o Python 3.

Nov 2nd 2026
5-12 Weeks
Principles of Computing (Part 2) (Coursera) Coursera
Rice University

Principles of Computing (Part 2) (Coursera)

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language. The main focus of the class will be weekly mini-projects that build upon the mathematical and programming principles that are taught in the class.

Nov 2nd 2026
4 Weeks