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Cours en Data Science

Les cours en data science peuvent vous aider à comprendre comment analyser des données, créer des modèles et évaluer leurs performances. Vous pouvez développer des compétences en statistique, apprentissage automatique, préparation des données et visualisation. De nombreux cours utilisent des langages et bibliothèques courants pour travailler sur des projets pratiques.


Cours et certificats populaires en Data Science


  • Status: Free Trial
    Free Trial
    G

    Google

    Foundations of Data Science

    Skills you'll gain: Data Ethics, Data-Driven Decision-Making, Data Analysis, Analytical Skills, Business Analytics, Data Storytelling, Data Science, Communication, Stakeholder Communications, Workflow Management, Project Management, Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.8K reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, Probability Distribution, R Programming, Biostatistics, Data Science, Statistics, Mathematical Modeling, Data Analysis, Data Modeling, Applied Mathematics

    4.4
    Rating, 4.4 out of 5 stars
    ·
    785 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Advanced Data Analytics

    Skills you'll gain: Data Storytelling, Data Visualization, Data Ethics, Exploratory Data Analysis, Sampling (Statistics), Data Visualization Software, Feature Engineering, Regression Analysis, Descriptive Statistics, Logistic Regression, Statistical Hypothesis Testing, Model Evaluation, Data Analysis, Tableau Software, Data Science, Statistical Analysis, Machine Learning, Object Oriented Programming (OOP), Interviewing Skills, 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
    C

    Corporate Finance Institute

    Practical Data Science for Data Analysts

    Skills you'll gain: Classification Algorithms, Data Preprocessing, Feature Engineering, Model Evaluation, Data Import/Export, Matplotlib, Data Science, Regression Analysis, Financial Data, Data Analysis, Exploratory Data Analysis, Business Analytics, Data Cleansing, Pandas (Python Package), Machine Learning Algorithms, Statistical Visualization, Financial Analysis, Statistical Modeling, Statistical Analysis, Predictive Analytics

    4.8
    Rating, 4.8 out of 5 stars
    ·
    28 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    MLOps | Machine Learning Operations

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

    4.2
    Rating, 4.2 out of 5 stars
    ·
    571 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    The Power of Statistics

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

    4.8
    Rating, 4.8 out of 5 stars
    ·
    866 reviews

    Advanced · Course · 1 - 3 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    More Applied Data Science with Python

    Skills you'll gain: Unsupervised Learning, Data Mining, Social Network Analysis, ChatGPT, Embeddings, Machine Learning Methods, Data Science, Supervised Learning, Generative AI, Machine Learning, Anomaly Detection, Data Preprocessing, Data Analysis, Recurrent Neural Networks (RNNs), Data Manipulation, Python Programming, Exploratory Data Analysis, Machine Learning Algorithms, Jupyter, Classification Algorithms

    4.3
    Rating, 4.3 out of 5 stars
    ·
    8 reviews

    Advanced · Specialization · 3 - 6 Months

  • Next level skills. New Year savings.

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  • Status: Free Trial
    Free Trial
    G

    Google

    Get Started with Python

    Skills you'll gain: Object Oriented Programming (OOP), Data Structures, Python Programming, NumPy, Pandas (Python Package), Data Analysis, Scripting, Data Manipulation, Data Visualization, Algorithms, Debugging

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1.8K reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    Google Business Intelligence

    Skills you'll gain: Data Modeling, Stakeholder Engagement, Database Design, Dashboard, Business Intelligence, Extract, Transform, Load, Tableau Software, Data Warehousing, Stakeholder Communications, Data Pipelines, Business Reporting, Data Mart, Data Visualization, Interviewing Skills, Applicant Tracking Systems, Business Process, AI Enablement, Business Analysis, Data Analysis, SQL

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6.8K reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM RAG and Agentic AI

    Skills you'll gain: Prompt Engineering, AI Orchestration, AI Workflows, Model Context Protocol, LangChain, Retrieval-Augmented Generation, Agentic Workflows, Tool Calling, LangGraph, LLM Application, Agentic systems, Multimodal Prompts, Generative AI, Generative AI Agents, Vector Databases, OpenAI API, Embeddings, Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), Software Development

    4.6
    Rating, 4.6 out of 5 stars
    ·
    664 reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Foundations of Data Structures and Algorithms

    Skills you'll gain: Theoretical Computer Science, Algorithms, Graph Theory, Data Structures, Operations Research, Public Key Cryptography Standards (PKCS), Cryptography, Programming Principles, Computational Thinking, Pseudocode, Design Strategies, Data Encryption Standard, Computer Science, Tree Maps, Encryption, Linear Algebra, Combinatorics, Mathematical Modeling, Advanced Mathematics, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    911 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Enterprise Workflow

    Skills you'll gain: Feature Engineering, Model Deployment, Data Visualization, Data Ethics, Exploratory Data Analysis, Model Evaluation, Unsupervised Learning, Data Presentation, Tensorflow, Dimensionality Reduction, MLOps (Machine Learning Operations), Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Data Science, Machine Learning, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    353 reviews

    Advanced · Specialization · 3 - 6 Months

What brings you to Coursera today?

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In summary, here are 10 of our most popular data science courses

  • Foundations of Data Science: Google
  • Advanced Statistics for Data Science: Johns Hopkins University
  • Google Advanced Data Analytics: Google
  • Practical Data Science for Data Analysts: Corporate Finance Institute
  • MLOps | Machine Learning Operations: Duke University
  • The Power of Statistics: Google
  • More Applied Data Science with Python: University of Michigan
  • Get Started with Python: Google
  • Google Business Intelligence: Google
  • IBM RAG and Agentic AI: IBM

Frequently Asked Questions about Data Science

Data science is an interdisciplinary field that combines statistics, computer science, and domain expertise to extract meaningful insights from data. It plays a crucial role in decision-making across various industries, helping organizations to understand trends, predict outcomes, and optimize processes. In today's data-driven world, the ability to analyze and interpret data is essential for businesses to remain competitive and innovative.‎

A career in data science can lead to various roles, including data analyst, data engineer, machine learning engineer, and data scientist. These positions are in high demand across sectors such as finance, healthcare, technology, and marketing. Each role focuses on different aspects of data, from data collection and cleaning to advanced analytics and predictive modeling, offering diverse opportunities for professionals.‎

To pursue a career in data science, you should develop a strong foundation in several key skills. These include programming languages like Python and R, statistical analysis, data visualization, and machine learning. Familiarity with databases and tools such as SQL and Tableau is also beneficial. Additionally, soft skills like problem-solving, critical thinking, and effective communication are essential for translating data insights into actionable strategies.‎

There are numerous online courses available for learning data science. Some of the best options include the IBM Data Science Professional Certificate, which covers essential skills and tools, and the Applied Data Science Specialization, which focuses on practical applications. These courses provide a structured learning path and hands-on experience to help you build your data science expertise.‎

Yes. You can start learning data science on Coursera for free in two ways:

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

To learn data science effectively, start by identifying your learning goals and the specific skills you want to acquire. Begin with foundational courses that cover basic concepts and gradually progress to more advanced topics. Engage in hands-on projects to apply your knowledge, and consider joining online communities or study groups to enhance your learning experience. Consistent practice and real-world application are key to mastering data science.‎

Data science courses typically cover a range of topics, including data manipulation, statistical analysis, machine learning, data visualization, and big data technologies. You may also encounter specialized subjects such as natural language processing, data ethics, and data engineering. This comprehensive curriculum prepares you to tackle various challenges in the field and equips you with the skills needed to analyze complex datasets.‎

For training and upskilling employees in data science, programs like the CertNexus Certified Data Science Practitioner Professional Certificate and the Fractal Data Science Professional Certificate are excellent choices. These courses are designed to enhance practical skills and provide a solid foundation in data science, making them suitable for workforce development.‎

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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