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  2. Machine Learning

Cours en Apprentissage automatique

Les cours en apprentissage automatique peuvent vous aider à comprendre comment construire, entraîner et analyser des modèles prédictifs. Vous pouvez développer des compétences en préparation des données, choix d'algorithmes, optimisation et évaluation. De nombreux cours utilisent des bibliothèques courantes pour tester des modèles.

Cours et certificats populaires en Apprentissage automatique


  • I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Applied Mathematics, Descriptive Statistics, Model Optimization, Statistics, Geometry, Artificial Neural Networks, Data Science, Data Manipulation, Python Programming, Data Transformation, Machine Learning, Derivatives

    4.6 stars, 15K reviews, Beginner, Specialization, 3 - 6 Months

    ★ 4.6 (15K) · Beginner · Specialization · 3 - 6 Months

    Status: Free trial
    Free trial
  • I

    IBM

    IBM Machine Learning

    Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Autoencoders, Feature Engineering, Dimensionality Reduction, Supervised Learning, Classification Algorithms, Regression Analysis, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Deep Learning, Data Science, Machine Learning, Python Programming

    4.6 stars, 3.7K reviews, Intermediate, Professional Certificate, 3 - 6 Months

    ★ 4.6 (3.7K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Top AI program
    Top AI program
    Status: Free trial
    Free trial
  • I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, Retrieval-Augmented Generation, PyTorch (Machine Learning Library), Computer Vision, Unsupervised Learning, Generative Model Architectures, Generative AI, Model Optimization, Keras (Neural Network Library), Supervised Learning, LLM Application, Generative AI Agents, Model Evaluation, Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science

    4.6 stars, 22K reviews, Intermediate, Professional Certificate, 3 - 6 Months

    ★ 4.6 (22K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Top AI program
    Top AI program
    Status: Free trial
    Free trial
  • D

    DeepLearning.AI

    AI For Everyone

    Skills you'll gain: Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, AI literacy, Machine Learning, Data Science, Deep Learning, Artificial Neural Networks

    4.8 stars, 53K reviews, Beginner, Course, 1 - 4 Weeks

    ★ 4.8 (53K) · Beginner · Course · 1 - 4 Weeks

    Status: Top AI program
    Top AI program
    Category: Preview
    Preview
  • Unlock 3 months of Google AI Pro at no extra cost today.

    Get started
  • C

    Coursera

    Machine Learning Pipelines with Azure ML Studio

    Skills you'll gain: Model Deployment, Decision Tree Learning, Applied Machine Learning, Predictive Modeling, Microsoft Azure, No-Code Development, Machine Learning, Data Preprocessing, Model Training, Cloud Deployment, Machine Learning Algorithms, Model Evaluation, Data Science, Data Analysis, Classification Algorithms

    4.5 stars, 836 reviews, Beginner, Guided Project, Less Than 2 Hours

    ★ 4.5 (836) · Beginner · Guided Project · Less Than 2 Hours

    Category: Free
    Free
  • What brings you to Coursera today?

  • I

    Imperial College London

    Mathematics for Machine Learning: Linear Algebra

    Skills you'll gain: Linear Algebra, Applied Machine Learning, Data Science, Data Manipulation, Data Transformation, Machine Learning

    4.6 stars, 13K reviews, Beginner, Course, 1 - 3 Months

    ★ 4.6 (13K) · Beginner · Course · 1 - 3 Months

    Status: Free trial
    Free trial
  • I

    IBM

    IBM AI Developer

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Unit Testing, Software Development Life Cycle, Generative AI, Retrieval-Augmented Generation, Large Language Modeling, Software Architecture, Responsible AI, Computer Vision, LangChain, LLM Application, Javascript, IBM Cloud, Data Ethics, Python Programming, Application Deployment, Software Development, Machine Learning, Data Science

    4.6 stars, 83K reviews, Beginner, Professional Certificate, 3 - 6 Months

    ★ 4.6 (83K) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Top AI program
    Top AI program
    Status: Free trial
    Free trial
  • J

    John Wiley & Sons

    Advanced Machine Learning, Neural Networks, and NLP

    Skills you'll gain: Supervised Learning, Machine Learning Methods, Applied Machine Learning, Computer Vision, Machine Learning Algorithms, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Natural Language Processing, Deep Learning, Artificial Neural Networks, Decision Tree Learning, Data Science, Logistic Regression, Data Preprocessing, Embeddings

    Advanced · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free trial
    Free trial
  • I

    IBM

    AI Foundations for Everyone

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Generative AI, Responsible AI, IBM Cloud, ChatGPT, AI literacy, Retrieval-Augmented Generation, Application Deployment, Artificial Intelligence and Machine Learning (AI/ML), AI Enablement, Workflow Management, Machine Learning, No-Code Development, Artificial Intelligence, Natural Language Processing, Deep Learning, Customer Service, AI Integrations, Data Science

    4.7 stars, 37K reviews, Beginner, Specialization, 3 - 6 Months

    ★ 4.7 (37K) · Beginner · Specialization · 3 - 6 Months

    Status: Top AI program
    Top AI program
    Status: Free trial
    Free trial
  • I

    IBM

    Exploratory Data Analysis for Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Methods, Data Preprocessing, Statistical Inference, Statistical Hypothesis Testing, Data Access, Statistics, Statistical Analysis, Data Analysis, Data Cleansing, Data Science, Machine Learning, Probability & Statistics, Artificial Intelligence

    4.6 stars, 2.6K reviews, Intermediate, Course, 1 - 3 Months

    ★ 4.6 (2.6K) · Intermediate · Course · 1 - 3 Months

    Status: Free trial
    Free trial
  • L

    LearnQuest

    No-Code Machine Learning and Data Science for Everyone

    Skills you'll gain: Responsible AI, Exploratory Data Analysis, Data Storytelling, Dashboard, Data Presentation, Model Evaluation, Dashboard Creation, Interactive Data Visualization, No-Code Development, Business Analytics, Data Science, Analytics, Model Training, Model Deployment, Model Optimization, Applied Machine Learning, Machine Learning, Data Analysis, Predictive Modeling, Data Visualization

    Beginner · Specialization · 1 - 3 Months

    Status: Free trial
    Free trial
  • C

    Coursera

    Data Science Challenge

    Skills you'll gain: Applied Machine Learning, Predictive Modeling, Model Evaluation, Model Optimization, Data Analysis, Machine Learning, Data Science, Python Programming

    4.7 stars, 230 reviews, Intermediate, Guided Project, Less Than 2 Hours

    ★ 4.7 (230) · Intermediate · Guided Project · Less Than 2 Hours

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Best Machine Learning courses from IBM

Top-rated Machine Learning courses offered by IBM on Coursera.

  1. 1
    IBM Machine Learning
    IBMIntermediate3 - 6 Months4.6(3,719)IBM
  2. 2
    IBM AI Engineering
    IBMIntermediate3 - 6 Months4.6(22,353)IBM
  3. 3
    IBM AI Developer
    IBMBeginner3 - 6 Months4.6(83,187)IBM

Best Machine Learning certificate programs

Earn a certificate in Machine Learning from top universities and companies.

  1. 1
    Mathematics for Machine Learning
    Imperial College LondonBeginner3 - 6 Months4.6(15,101)Specialization
  2. 2
    AI Foundations for Everyone
    IBMBeginner3 - 6 Months4.7(36,797)Specialization
  3. 3
    No-Code Machine Learning and Data Science for Everyone
    LearnQuestBeginner1 - 3 Months2.3(3)Specialization

Best Machine Learning courses for beginners

Top-rated beginner-friendly Machine Learning courses with no prerequisites.

  1. 1
    AI For Everyone
    DeepLearning.AIBeginner1 - 4 Weeks4.8(53,378)No prerequisites
  2. 2
    Machine Learning Pipelines with Azure ML Studio
    CourseraBeginnerLess Than 2 Hours4.5(836)No prerequisites
  3. 3
    Mathematics for Machine Learning: Linear Algebra
    Imperial College LondonBeginner1 - 3 Months4.6(12,615)No prerequisites

Frequently Asked Questions about Machine Learning

Machine learning is a subset of artificial intelligence that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention. It is important because it drives innovation across various sectors, from healthcare to finance, by automating processes and providing insights that were previously unattainable. As industries increasingly rely on data-driven decision-making, understanding machine learning becomes essential for staying competitive.‎

A variety of job opportunities exist in the field of machine learning. Positions include machine learning engineer, data scientist, AI researcher, and business intelligence analyst. These roles often require a blend of programming skills, statistical knowledge, and domain expertise. As organizations continue to adopt machine learning technologies, the demand for skilled professionals in this area is expected to grow.‎

To learn machine learning effectively, you should focus on several key skills. Proficiency in programming languages such as Python or R is crucial, along with a solid understanding of statistics and linear algebra. Familiarity with data manipulation and visualization tools, as well as experience with machine learning frameworks like TensorFlow or PyTorch, will also be beneficial. These skills will provide a strong foundation for your machine learning journey.‎

There are many excellent online resources for learning machine learning. Notable options include the IBM Machine Learning Professional Certificate and the Machine Learning with Scikit-learn, PyTorch & Hugging Face Professional Certificate. These programs offer structured learning paths and hands-on projects to help you build practical skills.‎

Yes. You can start learning Machine Learning on Coursera for free in two ways:

  1. Preview the first module of many Machine Learning 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 Machine Learning, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn machine learning, start by taking introductory courses that cover the basics of algorithms and data analysis. Engage in hands-on projects to apply what you've learned, and gradually progress to more advanced topics. Utilize online resources, participate in forums, and collaborate with peers to enhance your understanding. Consistent practice and real-world application will reinforce your skills.‎

Typical topics covered in machine learning courses include supervised and unsupervised learning, regression analysis, classification techniques, clustering, and neural networks. Additionally, courses often explore data preprocessing, feature engineering, and model evaluation. Understanding these concepts will equip you with the knowledge needed to tackle various machine learning challenges.‎

For training and upskilling employees in machine learning, programs like the Applied Machine Learning Specialization are highly effective. These courses focus on practical applications and real-world scenarios, making them suitable for professionals looking to enhance their skills and contribute to their organizations' data-driven initiatives.‎

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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