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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


  • I

    IBM

    Databases and SQL for Data Science with Python

    Skills you'll gain: SQL, Database Management, Relational Databases, Stored Procedure, Databases, Query Languages, Database Theory, Data Access, Jupyter, Data Manipulation, Data Analysis, Transaction Processing, Python Programming

    ★ 4.7 (23K) · Beginner · Course · 1 - 3 Months

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

    IBM

    Introduction to Data Science

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

    ★ 4.6 (102K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • I

    IBM

    IBM Data Science

    Skills you'll gain: Data Storytelling, Dashboard Creation, Data Presentation, Data Wrangling, Plotly, Data Visualization Software, Web Scraping, Data Visualization, Exploratory Data Analysis, SQL, Plot (Graphics), Dashboard, Unsupervised Learning, Interactive Data Visualization, Jupyter, Model Evaluation, Data Literacy, Generative AI, Professional Networking, Programming Principles

    ★ 4.6 (150K) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Build toward a degree
    Build toward a degree
  • I

    IBM

    Data Science Fundamentals with Python and SQL

    Skills you'll gain: Dashboard Creation, Web Scraping, SQL, Descriptive Statistics, Data Visualization, Statistical Analysis, Jupyter, Data Presentation, Probability Distribution, Data Analysis, R (Software), Statistics, Statistical Methods, Data Science, Database Management, Relational Databases, R Programming, Programming Principles, File I/O, Python Programming

    ★ 4.6 (75K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • I

    IBM

    IBM Data Analyst

    Skills you'll gain: Data Storytelling, Dashboard Creation, Data Presentation, Data Wrangling, Generative AI, Plotly, Data Visualization Software, Web Scraping, Data Visualization, Exploratory Data Analysis, SQL, Plot (Graphics), Dashboard, Data Analysis, Interviewing Skills, IBM Cognos Analytics, Excel Formulas, Programming Principles, Python Programming, Microsoft Excel

    ★ 4.6 (99K) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Build toward a degree
    Build toward a degree
  • C

    Coursera

    Python, SQL, Tableau for Data Science

    Skills you'll gain: Data Storytelling, Data Presentation, SQL, Data Visualization Software, Database Design, AWS SageMaker, Unsupervised Learning, Data Visualization, Interactive Data Visualization, Dashboard, Feature Engineering, Database Management, Exploratory Data Analysis, A/B Testing, Tableau Software, Pandas (Python Package), Matplotlib, Python Programming, Data Analysis, Machine Learning

    ★ 3.9 (26) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • I

    IBM

    Introduction to Data Engineering

    Skills you'll gain: Extract, Transform, Load, Data Store, Data Architecture, Data Pipelines, Big Data, Data Storage Technologies, Data Storage, Relational Databases, Data Infrastructure, Data Integration, Apache Hadoop, Data Warehousing, Databases, Data Lakes, SQL, Data Governance, Database Design, Apache Spark, NoSQL, Data Science

    ★ 4.7 (3.6K) · Beginner · Course · 1 - 4 Weeks

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

    Microsoft

    Microsoft Power BI Data Analyst

    Skills you'll gain: Dashboard Creation, Power BI, Microsoft Excel, Data Analysis, Data Integrity, Data Visualization, Data Storage, Microsoft Power Platform, Data Collection, Data Quality, Business Intelligence, Business Analytics, Advanced Analytics, Generative AI, Data Analysis Software, Statistical Reporting, Analytical Skills, Data Integration, Model Optimization, SQL

    ★ 4.6 (9.2K) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Build toward a degree
    Build toward a degree
  • U

    University of Michigan

    Python for Everybody

    Skills you'll gain: Database Design, Data Processing, Debugging, Web Scraping, File I/O, Data Visualization, Relational Databases, Restful API, Web Services, SQL, Databases, Data Visualization Software, JSON, Data Presentation, Extensible Markup Language (XML), Data Structures, Data Cleansing, Programming Principles, Python Programming, Program Development

    ★ 4.8 (280K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • I

    IBM

    SQL for Data Science with R

    Skills you'll gain: Database Design, Relational Databases, SQL, Database Development, Databases, R Programming, R (Software), Database Management, Data Science, Statistical Programming, Data Modeling, Query Languages, Data Manipulation, Data Analysis, Jupyter

    ★ 4.4 (192) · Beginner · Course · 1 - 3 Months

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

    IBM

    IBM Data Engineering

    Skills you'll gain: NoSQL, Extract, Transform, Load, Database Administration, Apache Spark, Data Warehousing, Web Scraping, Data Pipelines, Apache Hadoop, Database Architecture and Administration, Database Design, Database Management, Linux Commands, SQL, IBM Cognos Analytics, Generative AI, Professional Networking, Programming Principles, Python Programming, Data Analysis, Data Science

    ★ 4.6 (62K) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Build toward a degree
    Build toward a degree
  • G

    Google

    Google Business Intelligence

    Skills you'll gain: Data Modeling, Stakeholder Engagement, Database Design, Dashboard, Business Intelligence, Business Intelligence Software, Extract, Transform, Load, Dashboard Creation, Tableau Software, Databases, Data Warehousing, Stakeholder Communications, Data Visualization, Web Presence, Interviewing Skills, Business Process, Business Analysis, Professional Development, Data Analysis, SQL

    ★ 4.8 (8.1K) · Advanced · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
1234…51

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

  • Databases and SQL for Data Science with Python: IBM
  • Introduction to Data Science: IBM
  • IBM Data Science: IBM
  • Data Science Fundamentals with Python and SQL: IBM
  • IBM Data Analyst: IBM
  • Python, SQL, Tableau for Data Science: Coursera
  • Introduction to Data Engineering: IBM
  • Microsoft Power BI Data Analyst: Microsoft
  • Python for Everybody: University of Michigan
  • SQL for Data Science with R: 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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