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Cours en Informatique

Les cours en informatique peuvent vous aider à comprendre les algorithmes, les systèmes informatiques, les données et les principaux concepts liés au développement logiciel. Vous pouvez développer des compétences en raisonnement logique, modélisation, architecture et analyse. De nombreux cours utilisent des exemples concrets pour illustrer les principes fondamentaux.


Cours et certificats populaires en Informatique


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    Stanford University

    Algorithms

    Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Programming Principles, Social Network Analysis, Network Analysis, Computational Thinking, Analysis, Computer Science, Network Routing, Probability, Pseudocode, Computational Logic, Operations Research

    4.8
    Rating, 4.8 out of 5 stars
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    6K reviews

    Intermediate · Specialization · 3 - 6 Months

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    Stanford University

    AI in Healthcare

    Skills you'll gain: Feature Engineering, Healthcare Ethics, Pharmaceuticals, Data Ethics, Clinical Research, Clinical Data Management, Health Systems, Healthcare Industry Knowledge, Clinical Research Ethics, Unstructured Data, Health Care, Model Deployment, Health Informatics, Data Mining, Managed Care, Model Evaluation, Responsible AI, Applied Machine Learning, Machine Learning, Artificial Intelligence

    4.7
    Rating, 4.7 out of 5 stars
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    2.5K reviews

    Beginner · Specialization · 3 - 6 Months

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    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
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    38K reviews

    Beginner · Specialization · 1 - 3 Months

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    Stanford University

    Probabilistic Graphical Models

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Bayesian Statistics, Statistical Modeling, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Machine Learning Methods, Statistical Inference, Sampling (Statistics), Statistical Methods, Algorithms, Model Evaluation, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
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    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

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    DeepLearning.AI

    Unsupervised Learning, Recommenders, Reinforcement Learning

    Skills you'll gain: Unsupervised Learning, Data Ethics, Machine Learning, Supervised Learning, Artificial Intelligence, Reinforcement Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
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    5.5K reviews

    Beginner · Course · 1 - 4 Weeks

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    Stanford University

    Writing in the Sciences

    Skills you'll gain: Grant Writing, Peer Review, Technical Writing, Technical Communication, Writing, Scientific Methods, Journals, Editing, Grammar, Research, Proofreading, Healthcare Ethics, Media and Communications

    4.9
    Rating, 4.9 out of 5 stars
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    9.7K reviews

    Beginner · Course · 1 - 3 Months

What brings you to Coursera today?

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    DeepLearning.AI

    Supervised Machine Learning: Regression and Classification

    Skills you'll gain: Supervised Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Regression Analysis, Unsupervised Learning

    4.9
    Rating, 4.9 out of 5 stars
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    32K reviews

    Beginner · Course · 1 - 4 Weeks

  • Next level skills. New Year savings.

    Save on Coursera Plus
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    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
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    4.3K reviews

    Beginner · Course · 1 - 3 Months

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    Stanford University

    Social and Economic Networks: Models and Analysis

    Skills you'll gain: Social Network Analysis, Network Analysis, Sociology, Socioeconomics, Economics, Policy, and Social Studies, Game Theory, Mathematical Modeling, Statistical Modeling, Markov Model, Bayesian Statistics, Probability, Simulations

    4.8
    Rating, 4.8 out of 5 stars
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    759 reviews

    Advanced · Course · 1 - 3 Months

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    Stanford University

    Food Sustainability, Mindful Eating, and Healthy Cooking

    Skills you'll gain: Food and Beverage, Cooking, Sustainable Development, Nutrition and Diet, Cultural Diversity, Meal Planning And Preparation, Environment, Water Sustainability, Sustainability Standards, Nutrition Education, Sustainable Technologies, Resourcefulness, Mindfulness, Climate Change Mitigation, Waste Minimization, Adaptability, Environmental Science, Behavioral Health, Self-Awareness, Pollution Prevention

    4.8
    Rating, 4.8 out of 5 stars
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    603 reviews

    Beginner · Specialization · 1 - 3 Months

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    Stanford University

    Stanford Introduction to Food and Health

    Skills you'll gain: Cooking, Meal Planning And Preparation, Health Promotion, Health Education, Nutrition and Diet, Public Health, Behavior Management, Cultural Diversity, Health Informatics, Chronic Diseases

    4.7
    Rating, 4.7 out of 5 stars
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    34K reviews

    Beginner · Course · 1 - 3 Months

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    Stanford University

    Cryptography I

    Skills you'll gain: Cryptography, Data Encryption Standard, Encryption, Key Management, Advanced Encryption Standard (AES), Public Key Cryptography Standards (PKCS), Cybersecurity, Authentications, Data Integrity, Secure Coding, Algorithms, Computational Thinking

    4.8
    Rating, 4.8 out of 5 stars
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    4.5K reviews

    Mixed · Course · 1 - 3 Months

What brings you to Coursera today?

Searches related to computer science

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In summary, here are 10 of our most popular computer science courses

  • Algorithms: Stanford University
  • AI in Healthcare: Stanford University
  • Machine Learning: DeepLearning.AI
  • Probabilistic Graphical Models: Stanford University
  • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
  • Writing in the Sciences: Stanford University
  • Supervised Machine Learning: Regression and Classification : DeepLearning.AI
  • Introduction to Statistics: Stanford University
  • Social and Economic Networks: Models and Analysis: Stanford University
  • Food Sustainability, Mindful Eating, and Healthy Cooking: Stanford University

Frequently Asked Questions about Computer Science

Computer science is the study of computers and computational systems. It encompasses a wide range of topics, including algorithms, programming, data structures, and the theoretical foundations of information processing. The importance of computer science lies in its ability to drive innovation and efficiency across various industries. As technology continues to evolve, understanding computer science becomes crucial for solving complex problems, automating tasks, and creating new technologies that can enhance our daily lives.‎

A degree in computer science can open doors to numerous career opportunities. Common job roles include software developer, data analyst, systems analyst, and network administrator. Additionally, specialized positions such as machine learning engineer, cybersecurity analyst, and web developer are in high demand. The versatility of computer science allows professionals to work in various sectors, including finance, healthcare, education, and entertainment, making it a valuable field for those looking to build a rewarding career.‎

To succeed in computer science, you'll need a mix of technical and soft skills. Key technical skills include programming languages (such as Python, Java, or C++), understanding algorithms and data structures, and familiarity with databases and web development. Additionally, problem-solving skills, analytical thinking, and attention to detail are essential. Soft skills like communication and teamwork are also important, as many projects require collaboration with others.‎

There are many excellent online courses available for those interested in computer science. Some notable options include the Introduction to Computer Science and Programming Specialization and the Accelerated Computer Science Fundamentals Specialization. These courses provide foundational knowledge and practical skills that can help you start your journey in computer science.‎

Yes. You can start learning computer science on Coursera for free in two ways:

  1. Preview the first module of many computer science courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in computer science, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn computer science, start by identifying your interests and goals. You can begin with foundational courses that cover programming basics and algorithms. Utilize online platforms like Coursera to find structured courses that fit your learning style. Engage in hands-on projects to apply what you learn, and consider joining online communities or study groups for support and motivation.‎

Computer science courses typically cover a variety of topics, including programming languages, algorithms, data structures, software engineering, and computer architecture. Advanced courses may explore areas like artificial intelligence, machine learning, and cybersecurity. This breadth of topics ensures that learners gain a comprehensive understanding of the field and its applications.‎

For training and upskilling employees, courses like the Foundations of Computer Science and Computer Science: Programming with a Purpose are excellent choices. These courses provide essential skills that can enhance productivity and innovation within the workforce, making them valuable for organizations looking to invest in their employees' development.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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