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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


  • Status: Free Trial
    Free Trial
    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, Machine Learning Methods, Model Training, Random Forest Algorithm, Model Optimization, Data Analysis, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    617 reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
    New
    G

    Google

    Google AI

    Skills you'll gain: Vibe coding, Prompt Patterns, AI powered creativity, Brainstorming, Planning, AI literacy, Visual Storytelling, Responsible AI, Prompt Engineering Tools, Generative AI, Data Wrangling, Data Analysis, Content Creation, Artificial Intelligence, Presentations, Business Communication, Data Visualization, Research, Project Management, Machine Learning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    2.9K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    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

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    11K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    G

    Google

    Google AI Essentials

    Skills you'll gain: Prompt Patterns, Google Gemini, Generative AI, AI literacy, Model Training, AI Integrations, Google Sheets, Critical Thinking, Innovation

    4.8
    Rating, 4.8 out of 5 stars
    ·
    21K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Crash Course on Python

    Skills you'll gain: Program Development, Programming Principles, Scripting Languages, Scripting, Python Programming, Computer Programming, Computational Thinking, Data Structures, Data Store, Integrated Development Environments, Debugging, Computer Programming Tools, Development Environment

    4.8
    Rating, 4.8 out of 5 stars
    ·
    40K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Introduction to AI

    Skills you'll gain: Generative AI, AI Enablement, Artificial Intelligence and Machine Learning (AI/ML), AI literacy, Model Training, Machine Learning, Innovation, Critical Thinking

    4.8
    Rating, 4.8 out of 5 stars
    ·
    12K reviews

    Beginner · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    G

    Google

    Google Cybersecurity

    Skills you'll gain: Threat Modeling, Network Security, Threat Management, Vulnerability Management, Intrusion Detection and Prevention, Hardening, Computer Security Incident Management, Security Management, Cyber Threat Intelligence, Security Awareness, Incident Response, Cybersecurity, Network Protocols, Endpoint Detection and Response, Bash (Scripting Language), Debugging, Linux, Web Presence, Python Programming, SQL

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    66K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    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, Data Science, Statistical Inference, Statistical Programming, Statistical Methods, Probability, Python Programming

    4.8
    Rating, 4.8 out of 5 stars
    ·
    890 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    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
    Rating, 4.8 out of 5 stars
    ·
    54K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Speed Up Data Analysis and Presentation Building

    Skills you'll gain: Data Visualization, Data Presentation, Responsible AI, Prompt Engineering, Graphing, Prompt Patterns, Data Analysis, Spreadsheet Software

    4.8
    Rating, 4.8 out of 5 stars
    ·
    887 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google

    Create a High-Performing Team

    Skills you'll gain: People Management, Team Leadership, Team Management, Management Training And Development, Team Performance Management, Team Building, Leadership and Management, Organizational Leadership, Teamwork, Relationship Management, Leadership, Culture Transformation, Organizational Effectiveness, Relationship Building, Internal Communications, Communication Strategies, Willingness To Learn, Lifelong Learning, AI Enablement

    4.8
    Rating, 4.8 out of 5 stars
    ·
    257 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Data Analysis with Python

    Skills you'll gain: Pandas (Python Package), NumPy, Data Manipulation, Code Reusability, Data Preprocessing, Data Wrangling, Package and Software Management, Data Analysis, Data Processing, Data Integration, JSON, Object Oriented Programming (OOP), Data Science, Data Structures, Python Programming, Exploratory Data Analysis, Computer Programming, Programming Principles, Data Storage, Computational Logic

    4.8
    Rating, 4.8 out of 5 stars
    ·
    130 reviews

    Beginner · Specialization · 3 - 6 Months

1234

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

  • The Nuts and Bolts of Machine Learning: Google
  • Google AI: Google
  • Google Advanced Data Analytics: Google
  • Google AI Essentials: Google
  • Crash Course on Python: Google
  • Introduction to AI: Google
  • Google Cybersecurity: Google
  • The Power of Statistics: Google
  • Google IT Automation with Python: Google
  • Speed Up Data Analysis and Presentation Building: 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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