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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


  • 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, Artificial Intelligence, Amazon Web Services, Applied Machine Learning, AI literacy, Machine Learning, Digital Transformation

    ★ 4.6 (3.2K) · Mixed · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
  • A

    Amazon Web Services

    Developing Machine Learning Solutions

    Skills you'll gain: Model Evaluation, MLOps (Machine Learning Operations), Model Training, Amazon Web Services, AI Workflows, Model Deployment, Machine Learning Methods, Machine Learning, Applied Machine Learning

    ★ 4.5 (116) · Beginner · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
  • A

    Amazon Web Services

    Planning a Machine Learning Project

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

    ★ 4.6 (21) · Mixed · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
  • A

    Amazon Web Services

    Machine Learning Essentials for Business and Technical Decision Makers

    Skills you'll gain: Machine Learning Methods, Decision Intelligence, Applied Machine Learning, Machine Learning, Technology Roadmaps, Data-Driven Decision-Making, Artificial Intelligence and Machine Learning (AI/ML), Business Solutions, Organizational Strategy, AI Product Strategy, Organizational Change, Feasibility Studies

    ★ 4.9 (14) · Beginner · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
  • A

    Amazon Web Services

    AWS Cloud Solutions Architect

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

    ★ 4.8 (7.1K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • 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, Fine-tuning, LangChain, AI Workflows, Agentic Workflows, Model Training, Model Optimization, Large Language Modeling, Artificial Intelligence, Token Optimization, Transfer Learning, LLM Application, AI literacy, Amazon Web Services, Context Management

    ★ 4.6 (90) · Intermediate · Professional Certificate · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • A

    Amazon Web Services

    AWS Generative AI Applications

    Skills you'll gain: Responsible AI, Generative AI, Generative AI Agents, Prompt Engineering, Amazon Bedrock, Data Ethics, AWS SageMaker, AI Workflows, Agentic systems, AI Product Strategy, Agentic Workflows, Amazon Web Services, AI Integrations, LLM Application, AI Orchestration, MLOps (Machine Learning Operations), Application Programming Interface (API), Application Development, Solution Architecture, Data Management

    ★ 4.6 (120) · Beginner · Professional Certificate · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Credit offered
    Credit offered
  • A

    Amazon Web Services

    Introduction to Machine Learning: Art of the Possible

    Skills you'll gain: Business Leadership, Strategic Leadership, Strategic Decision-Making, Business Transformation, Applied Machine Learning, Business Strategy, Business Planning, AI Enablement, Leadership and Management, Machine Learning, Process Development, Decision Making, Technology Roadmaps

    ★ 4.3 (20) · Beginner · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
  • D
    A

    Multiple educators

    DeepLearning.AI Data Engineering

    Skills you'll gain: Data Store, Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Storage Technologies, Data Architecture, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Data Preprocessing, Apache Hadoop, Requirements Elicitation, Vector Databases, Extract, Transform, Load, Data Lakes, Data Integration, Infrastructure as Code (IaC), Data Management

    ★ 4.7 (588) · Intermediate · Professional Certificate · 3 - 6 Months

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

    Amazon Web Services

    Fundamentals of Analytics on AWS

    Skills you'll gain: Data-Driven Decision-Making, Data Lakes, Data Storage Technologies, Analytics, Data Architecture, Data Warehousing, Data Management, Data Analysis, Big Data, Data Storage, Amazon Web Services, Machine Learning

    ★ 4.5 (66) · Mixed · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
  • D

    DeepLearning.AI

    Generative AI with Large Language Models

    Skills you'll gain: Generative AI, Large Language Modeling, Generative Model Architectures, Fine-tuning, LLM Application, Model Training, Model Deployment, Python Programming, Scalability, Model Optimization, Machine Learning, Model Evaluation, Reinforcement Learning

    ★ 4.8 (3.6K) · Intermediate · Course · 1 - 4 Weeks

    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • A

    Amazon Web Services

    Exploring Artificial Intelligence Use Cases and Applications

    Skills you'll gain: Generative AI, Business Metrics, Generative Model Architectures, Machine Learning Methods, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, AI literacy, Model Evaluation, LLM Application, Artificial Intelligence, Key Performance Indicators (KPIs), Performance Measurement, Performance Metric, Business Solutions

    ★ 4.5 (265) · Beginner · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
12345

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 and AI Agents with Amazon Bedrock: Amazon Web Services
  • AWS Generative AI Applications: Amazon Web Services
  • Introduction to Machine Learning: Art of the Possible: Amazon Web Services
  • DeepLearning.AI Data Engineering: DeepLearning.AI
  • Fundamentals of Analytics on AWS: 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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