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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
    I

    IBM

    Python for Data Science, AI & Development

    Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Application Programming Interface (API), Automation, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    43K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    What is Data Science?

    Skills you'll gain: Data Literacy, Data Mining, Big Data, Cloud Computing, Data Analysis, Data Science, Digital Transformation, Data-Driven Decision-Making, Deep Learning, Machine Learning, Artificial Intelligence

    4.7
    Rating, 4.7 out of 5 stars
    ·
    77K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Data Science Beyond the Basics (ML+DS)

    Skills you'll gain: Generative AI, Model Evaluation, Supervised Learning, Generative Model Architectures, AWS SageMaker, Recurrent Neural Networks (RNNs), Unsupervised Learning, Data Preprocessing, Large Language Modeling, Time Series Analysis and Forecasting, LLM Application, Applied Machine Learning, Deep Learning, A/B Testing, Transfer Learning, Python Programming, Machine Learning, Data Analysis, AWS CloudFormation, AI Personalization

    4.2
    Rating, 4.2 out of 5 stars
    ·
    23 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM Data Science

    Skills you'll gain: Exploratory Data Analysis, Dashboard, Data Visualization Software, Data Visualization, Model Evaluation, SQL, Unsupervised Learning, Interactive Data Visualization, Data Transformation, Supervised Learning, Jupyter, Data Analysis, Data Cleansing, Data Manipulation, Data Literacy, Plotly, Data Mining, Generative AI, Professional Networking, Data Import/Export

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    149K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • 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
    I

    IBM

    Introduction to Data Science

    Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Data Modeling, Relational Databases, Stored Procedure, Model Deployment, Databases, Data Science, Big Data, Computer Programming Tools, Query Languages, Data Visualization Software, GitHub, Data Preprocessing, Data Cleansing, R (Software), Cloud Computing, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    101K reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    I

    IBM

    Databases and SQL for Data Science with Python

    Skills you'll gain: SQL, Relational Databases, Stored Procedure, Databases, Query Languages, Jupyter, Data Manipulation, Data Analysis, Pandas (Python Package), Transaction Processing, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    23K reviews

    Beginner · Course · 1 - 3 Months

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Data Science

    Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Model Evaluation, Regression Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Machine Learning Algorithms, Plotly, Plot (Graphics), Interactive Data Visualization, Machine Learning, GitHub

    4.5
    Rating, 4.5 out of 5 stars
    ·
    51K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Applied Data Science with Python

    Skills you'll gain: Matplotlib, Network Analysis, Social Network Analysis, Feature Engineering, Data Visualization, Pandas (Python Package), Data Visualization Software, Interactive Data Visualization, Model Evaluation, Scientific Visualization, Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Data Manipulation, NumPy, Graph Theory, Data Preprocessing, Natural Language Processing, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    34K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I
    U
    I

    Multiple educators

    Data Science Foundations

    Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Data Presentation, Correlation Analysis, Web Scraping, NumPy, Data Import/Export, Probability & Statistics, Programming Principles, Predictive Modeling, Computer Programming Tools, Data Science, Unsupervised Learning, Machine Learning, Project Management

    4.6
    Rating, 4.6 out of 5 stars
    ·
    117K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of California, Davis

    SQL for Data Science

    Skills you'll gain: Data Governance, SQL, Data Management, Data Quality, Database Design, Query Languages, Data Literacy, Data Manipulation, Data Modeling, Relational Databases, Data Science, Databases, Data Analysis, Data Transformation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    17K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Data Science Fundamentals with Python and SQL

    Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Presentation, Statistics, Data Visualization, Relational Databases, Stored Procedure, Data Import/Export, Data Science, Programming Principles, Computer Programming Tools, Web Scraping, Data Visualization Software, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    75K reviews

    Beginner · 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

  • Python for Data Science, AI & Development: IBM
  • What is Data Science? : IBM
  • Data Science Beyond the Basics (ML+DS): Coursera
  • IBM Data Science: IBM
  • Foundations of Data Science: Google
  • Introduction to Data Science: IBM
  • Databases and SQL for Data Science with Python: IBM
  • Data Science: Johns Hopkins University
  • Applied Data Science with Python: University of Michigan
  • Data Science Foundations: 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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