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  • 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


  • G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

    ★ 4.8 (617) · Advanced · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, GitHub Copilot, Unit Testing, Responsible AI, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    ★ 4.2 (606) · Advanced · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    IBM RAG and Agentic AI

    Skills you'll gain: Prompt Engineering, AI Orchestration, AI Workflows, LangChain, Retrieval-Augmented Generation, Agentic Workflows, Tool Calling, LangGraph, LLM Application, Prompt Patterns, Agentic systems, Multimodal Prompts, Model Context Protocol, Generative AI, AI Security, Generative AI Agents, Vector Databases, OpenAI API, AI Integrations, Software Development

    ★ 4.6 (885) · Advanced · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Advanced Machine Learning on Google Cloud

    Skills you'll gain: Model Deployment, Model Optimization, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Model Training, Transfer Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Machine Learning

    ★ 4.5 (1.5K) · Advanced · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google

    Google Advanced Data Analytics

    Skills you'll gain: Data Storytelling, Data Visualization, A/B Testing, Sampling (Statistics), Data Analysis, Exploratory Data Analysis, Regression Analysis, Data Visualization Software, Data Presentation, Data Ethics, Feature Engineering, Statistical Hypothesis Testing, Analytics, Statistical Analysis, Data Science, Tableau Software, Machine Learning, Object Oriented Programming (OOP), Web Presence, Python Programming

    ★ 4.8 (11K) · Advanced · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • I

    IBM

    Machine Learning Capstone

    Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Machine Learning Methods, Applied Machine Learning, Predictive Modeling, Data Presentation, AI Personalization, Machine Learning, Data Analysis, Predictive Analytics, Machine Learning Software, Technical Communication, Machine Learning Algorithms, Statistical Analysis, Scikit Learn (Machine Learning Library), Keras (Neural Network Library), Descriptive Statistics, Regression Analysis, Python Programming

    ★ 4.7 (202) · Advanced · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • S

    SAS

    SAS Machine Learning Engineer

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Data Preprocessing, Classification And Regression Tree (CART), Exploratory Data Analysis, Logistic Regression, Statistical Machine Learning, Model Evaluation, Model Training, Supervised Learning, Decision Tree Learning, Probability & Statistics, Data Processing, Machine Learning Software, Statistical Software, Machine Learning Methods, Process Modeling, Machine Learning, Correlation Analysis, Applied Machine Learning

    ★ 4.7 (105) · Advanced · Professional Certificate · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of Toronto

    Self-Driving Cars

    Skills you'll gain: Computer Vision, Convolutional Neural Networks, Image Analysis, Control Systems, Robotics, Embedded Software, Automation, Deep Learning, Software Architecture, Safety Assurance, Global Positioning Systems, Hardware Architecture, Systems Architecture, Network Routing, Graph Theory, Estimation, Algorithms, Simulations, Mathematical Modeling, Linear Algebra

    ★ 4.7 (3.6K) · Advanced · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of Illinois Urbana-Champaign

    Deep Learning for Healthcare

    Skills you'll gain: Deep Learning, Convolutional Neural Networks, Health Informatics, Autoencoders, Recurrent Neural Networks (RNNs), Generative AI, Image Analysis, Machine Learning Methods, Embeddings, Generative Model Architectures, Machine Learning, Applied Machine Learning, Machine Learning Algorithms, Model Deployment, Artificial Neural Networks, Supervised Learning, Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Health Care, Big Data

    ★ 3.3 (49) · Advanced · Specialization · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google

    The Power of Statistics

    Skills you'll gain: A/B Testing, Sampling (Statistics), Data Analysis, Analytics, Statistics, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Probability & Statistics, Statistical Software, Advanced Analytics, Probability Distribution, Statistical Inference, Data Science, Statistical Programming, Statistical Methods, Probability, Python Programming

    ★ 4.8 (890) · Advanced · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google

    Google IT Automation with Python

    Skills you'll gain: Git (Version Control System), GitHub, Version Control, Infrastructure as Code (IaC), Debugging, Cloud Management, Bash (Scripting Language), Test Automation, Puppet (Configuration Management Tool), Infrastructure As A Service (IaaS), Technical Communication, Web Services, Email Automation, Web Presence, Automation, Python Programming, Interviewing Skills, Configuration Management, Program Development, Programming Principles

    ★ 4.8 (54K) · Advanced · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • P

    Packt

    Applied Machine Learning and Model Optimization

    Skills you'll gain: Supervised Learning, Model Optimization, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Predictive Modeling, Model Training, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Data Transformation, Fine-tuning

    Advanced · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1234…28

In summary, here are 10 of our most popular machine learning courses

  • The Nuts and Bolts of Machine Learning: Google
  • MLOps | Machine Learning Operations: Duke University
  • IBM RAG and Agentic AI: IBM
  • Advanced Machine Learning on Google Cloud: Google Cloud
  • Google Advanced Data Analytics: Google
  • Machine Learning Capstone: IBM
  • SAS Machine Learning Engineer: SAS
  • Self-Driving Cars: University of Toronto
  • Deep Learning for Healthcare: University of Illinois Urbana-Champaign
  • The Power of Statistics: Google

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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