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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


  • Status: Free
    Free
    A

    Amazon Web Services

    Fundamentals of Machine Learning and Artificial Intelligence

    Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, AI Enablement, Artificial Intelligence, Amazon Web Services, Applied Machine Learning, Machine Learning, Digital Transformation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.5K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free
    Free
    A

    Amazon Web Services

    Developing Machine Learning Solutions

    Skills you'll gain: Model Evaluation, MLOps (Machine Learning Operations), AWS SageMaker, Amazon Web Services, Model Deployment, Machine Learning, Applied Machine Learning, Predictive Modeling

    4.5
    Rating, 4.5 out of 5 stars
    ·
    102 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free
    Free
    A

    Amazon Web Services

    Planning a Machine Learning Project

    Skills you'll gain: Feasibility Studies, Business Analysis, Business Analytics, Decision Making, Strategic Decision-Making, Data-Driven Decision-Making, Machine Learning, Strategic Thinking, Business Leadership, Project Planning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    20 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free
    Free
    A

    Amazon Web Services

    Machine Learning Essentials for Business and Technical Decision Makers

    Skills you'll gain: Applied Machine Learning, Machine Learning, AI Enablement, MLOps (Machine Learning Operations), Technology Roadmaps, Data-Driven Decision-Making, Artificial Intelligence and Machine Learning (AI/ML), Business Analytics, Business Solutions, Organizational Strategy, AI Product Strategy, Organizational Change, Product Roadmaps, Feasibility Studies, System Requirements, Solution Design, Training Programs

    4.8
    Rating, 4.8 out of 5 stars
    ·
    10 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    A

    Amazon Web Services

    AWS Cloud Solutions Architect

    Skills you'll gain: AWS Identity and Access Management (IAM), Amazon CloudWatch, Data Lakes, Amazon DynamoDB, Amazon Web Services, Serverless Computing, Cloud Computing, Amazon S3, Scalability, Cloud Infrastructure, Amazon Elastic Compute Cloud, Event-Driven Programming, Cloud Security, Solution Architecture, Data Visualization, Cloud Storage, Data Architecture, Cloud Computing Architecture, API Gateway, Software Architecture

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    7K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    A

    Amazon Web Services

    AWS Generative AI Applications

    Skills you'll gain: Responsible AI, Generative AI, Prompt Engineering, Amazon Bedrock, AWS SageMaker, AI Workflows, Agentic systems, AI Enablement, AI Product Strategy, Generative AI Agents, Amazon Web Services, AI Orchestration, Application Programming Interface (API), Application Development, Model Deployment, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, LLM Application, Solution Architecture, Data Management

    4.6
    Rating, 4.6 out of 5 stars
    ·
    102 reviews

    Beginner · Professional Certificate · 1 - 3 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    A

    Amazon Web Services

    AWS Generative AI and AI Agents with Amazon Bedrock

    Skills you'll gain: Amazon Bedrock, Prompt Engineering, Responsible AI, Generative AI Agents, Retrieval-Augmented Generation, Generative AI, LangChain, AI Workflows, AI Orchestration, Artificial Intelligence and Machine Learning (AI/ML), Large Language Modeling, Applied Machine Learning, Transfer Learning, LLM Application, Embeddings, Amazon Web Services, Context Management, Model Deployment, Amazon S3, Model Evaluation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    70 reviews

    Intermediate · Professional Certificate · 1 - 3 Months

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: Free
    Free
    A

    Amazon Web Services

    Introduction to Machine Learning: Art of the Possible

    Skills you'll gain: Strategic Leadership, Strategic Decision-Making, Business Transformation, Business Strategy, Data-Driven Decision-Making, AI Enablement, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Decision Making, Technology Roadmaps

    4.1
    Rating, 4.1 out of 5 stars
    ·
    17 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free
    Free
    A

    Amazon Web Services

    Optimizing Foundation Models

    Skills you'll gain: Retrieval-Augmented Generation, Embeddings, Vector Databases, Amazon Web Services, Agentic systems, Performance Tuning, Transfer Learning, Data Preprocessing

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Preview
    Preview
    A

    Amazon Web Services

    AWS Generative AI Lab Series

    Skills you'll gain: Prompt Engineering, Amazon Bedrock, AWS SageMaker, Generative AI, Multimodal Prompts, Artificial Intelligence and Machine Learning (AI/ML), Large Language Modeling, Applied Machine Learning, Scikit Learn (Machine Learning Library), Image Analysis, Real Time Data

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    A

    Amazon Web Services

    AWS Cloud Technical Essentials

    Skills you'll gain: AWS Identity and Access Management (IAM), Amazon CloudWatch, Amazon DynamoDB, Amazon Web Services, Cloud Computing, Amazon S3, Scalability, Cloud Infrastructure, Amazon Elastic Compute Cloud, Cloud Security, Cloud Computing Architecture, Serverless Computing, Cloud Storage, Databases, Virtual Networking, General Networking, Containerization

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6.2K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D
    A

    Multiple educators

    DeepLearning.AI Data Engineering

    Skills you'll gain: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Architecture, Requirements Analysis, Data Warehousing, Query Languages, Data Preprocessing, Apache Hadoop, Vector Databases, Data Lakes, Amazon Web Services, File Systems, Apache Spark, Database Systems, Feature Engineering, Dataflow, Data Integration, Data Management

    4.7
    Rating, 4.7 out of 5 stars
    ·
    575 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

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

  • Fundamentals of Machine Learning and Artificial Intelligence: Amazon Web Services
  • Developing Machine Learning Solutions: Amazon Web Services
  • Planning a Machine Learning Project: Amazon Web Services
  • Machine Learning Essentials for Business and Technical Decision Makers: Amazon Web Services
  • AWS Cloud Solutions Architect: Amazon Web Services
  • AWS Generative AI Applications: Amazon Web Services
  • AWS Generative AI and AI Agents with Amazon Bedrock: Amazon Web Services
  • Introduction to Machine Learning: Art of the Possible: Amazon Web Services
  • Optimizing Foundation Models: Amazon Web Services
  • AWS Generative AI Lab Series: Amazon Web Services

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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