REAMOOC

Eléments de base d’informatique pour l’algorithmique (REAMOOC)

Offered by National Advanced School of Engineering, Yaounde,
Eléments de base d’informatique pour l’algorithmique (REAMOOC)

Ce MOOC Présente les concepts fondamentaux d'informatique pour aborder un cours d'algorithmique de première année de filière scientifique des universités et grandes écoles. Les notions abordées sont: 1- Information et Informatique 2- Représentation de l'information 3- Algorithme et sous-algorithme

MOOC Eléments de Base d'Informatique pour l'Algorithmique ou EBIA
Le MOOC EBIA présente aux élèves qui sollicitent l'entrée en première année des filières scientifiques des universités et grandes écoles, des notions de base d'informatique importantes pour aborder sereinement le cours d'algorithmique. Il a été développé dans le cadre du projet REAMOOC (REseau Africain de développement de MOOCs).

Projet REAMOOC
REAMOOC est un projet co-financé par le programme Erasmus+ de l’Union Européenne, co-coordonné par l’Université Libre de Bruxelles et l’Agence Universitaire de la Francophonie. Il regroupe douze partenaires dont six universités africaines pilotes que sont les universités Cheick-Anta Diop, Gaston-Berger et l’Université Virtuelle du Sénégal au Sénégal, et les universités de Douala, N’Gaoundéré et Yaoundé 1 au Cameroun.

Objectif du MOOC
L'objectif général de ce MOOC est de permettre aux étudiants d'acquérir les compétences suivantes :

  • Choisir un système informatique pour un usage personnel ou de service
  • Juger de la capacité d’un système à faciliter l’exécution d’une tâche
  • Concevoir les processus pouvant être exécuter par un système informatique
  • Séquencer ses activités avec rigueur
  • Choisir le système de stockage de l’information

L'acquisition de ces compétences passe par la compréhension et l'application des sujets suivants qui constituent les chapeaux des modules :

  • Informatique et ordinateur
  • Présentation de l'information
  • Algorithmique: structures de contrôle et sous-algorithme

Plan du cours

Le MOOC dure quatre semaines dont trois semaines de cours et une semaine dédiée au Certificat.
Semaine 1 :
Module 0 : Présentation du MOOC
Module 1 : Informatique et ordinateur
Evaluation sommative
Semaine 2 :
Module 2 : Présentation de l'information en machine
Evaluation sommative
Semaine 3 :
Module 3 : Algorithmique: structures de contrôle et sous-algorithme
Evaluation sommative
Semaine 4 :
Certificat

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

Related Courses

Analytic Combinatorics (Coursera) Coursera
Princeton University

Analytic Combinatorics (Coursera)

CS: Theory Sci: Mathematics

Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations. All the features of this course are available for free. It does not offer a certificate upon completion.

Nov 2nd 2026
5-12 Weeks
Math Calculus Analytic Combinatorics
Details
Approximation Algorithms (Coursera) Coursera
EIT Digital

Approximation Algorithms (Coursera)

Computer Science

Many real-world algorithmic problems cannot be solved efficiently using traditional algorithmic tools, for example because the problems are NP-hard. The goal of this course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. These techniques apply when we don't require the optimal solution to certain problems, but an approximation that is close to the optimal solution. We will see how to efficiently find such approximations.

Nov 13th 2026
4 Weeks
Algorithms Approximation Algorithms LP Relaxation
Details
An Introduction to Cryptography (Coursera) Coursera
University of Leeds

An Introduction to Cryptography (Coursera)

Computer Science

Cryptography is an essential part of secure but accessible communication that's critical for our everyday life and organisations use it to protect their privacy and keep their conversations and data confidential. This course provides a comprehensive introduction to the fascinating world of cryptography, covering both historical cyphers and modern-day cryptographic techniques.

Nov 16th 2026
2 Weeks
Cryptography Algorithms Encryption
Details
Algorithms, Part II (Coursera) Coursera
Princeton University

Algorithms, Part II (Coursera)

CS: Software Engineering CS: Theory

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.

Nov 9th 2026
5-12 Weeks
Java Algorithms Data Structures
Details
Principles of Computing (Part 2) (Coursera) Coursera
Rice University

Principles of Computing (Part 2) (Coursera)

CS: Software Engineering CS: Theory

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
Programming Python Computing
Details
VLSI CAD Part II: Layout (Coursera) Coursera
University of Illinois at Urbana-Champaign

VLSI CAD Part II: Layout (Coursera)

CS: Software Engineering CS: Theory

A modern VLSI chip is a remarkably complex beast: billions of transistors, millions of logic gates deployed for computation and control, big blocks of memory, embedded blocks of pre-designed functions designed by third parties (called “intellectual property” or IP blocks). How do people manage to design these complicated chips? Answer: a sequence of computer aided design (CAD) tools takes an abstract description of the chip, and refines it step-wise to a final design.

Nov 16th 2026
5-12 Weeks
Programming Algorithms ASIC
Details
How Computers Work (Coursera) Coursera
University of London,Goldsmiths, University of London

How Computers Work (Coursera)

Security & Networking

Computers are everywhere, they aren't just the desktops and laptops we use for work but the phones in our pockets and even the watches on our wrists are also computers. You probably use a computer every day and in fact you are reading this on a computer! Just because we use computers all the time, doesn't mean that we understand them, or find them easy to use. Computer Science is the science of computers, it is the field of knowledge that experts use to understand computer systems. Knowing a little computer science will help you understand the computers all around you.

Nov 16th 2026
4 Weeks
Computer Networks Computer Science
Details
Problem Solving Using Computational Thinking (Coursera) Coursera
University of Michigan

Problem Solving Using Computational Thinking (Coursera)

CS: Theory Computer Science

Have you ever heard that computers "think"? Believe it or not, computers really do not think. Instead, they do exactly what we tell them to do. Programming is, "telling the computer what to do and how to do it." Before you can think about programming a computer, you need to work out exactly what it is you want to tell the computer to do. Thinking through problems this way is Computational Thinking. Computational Thinking allows us to take complex problems, understand what the problem is, and develop solutions. We can present these solutions in a way that both computers and people can understand.

Nov 9th 2026
5-12 Weeks
Programming Algorithms Computational Thinking
Details
Practical Steps for Building Fair AI Algorithms (Coursera) Coursera
Fred Hutchinson Cancer Center

Practical Steps for Building Fair AI Algorithms (Coursera)

Computer Science

Algorithms increasingly help make high-stakes decisions in healthcare, criminal justice, hiring, and other important areas. This makes it essential that these algorithms be fair, but recent years have shown the many ways algorithms can have biases by age, gender, nationality, race, and other attributes. This course will teach you ten practical principles for designing fair algorithms. It will emphasize real-world relevance via concrete takeaways from case studies of modern algorithms, including those in criminal justice, healthcare, and large language models like ChatGPT. You will come away with an understanding of the basic rules to follow when trying to design fair algorithms, and assess algorithms for fairness.

Nov 9th 2026
4 Weeks
Algorithms Algorithm Design Bias
Details