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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.


More to explore:

Cours et certificats populaires en Data Science


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

    IBM

    IBM Data Science

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

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    150K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • 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

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Data Science

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

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    102K 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, Web Scraping, SQL, Descriptive Statistics, Data Visualization, Statistical Analysis, Jupyter, Probability Distribution, Data Analysis, R (Software), Statistics, Statistical Hypothesis Testing, Data Science, Statistical Programming, Relational Databases, Stored Procedure, R Programming, Data Import/Export, Programming Principles, Python Programming

    Build toward a degree

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

    Beginner · Specialization · 3 - 6 Months

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

    IBM

    IBM Data Analyst

    Skills you'll gain: Data Storytelling, Dashboard, Data Presentation, Plotly, Data Visualization Software, Web Scraping, Data Visualization, Exploratory Data Analysis, Generative AI, SQL, Data Wrangling, Interactive Data Visualization, Data Analysis, Data Manipulation, IBM Cognos Analytics, Excel Formulas, Professional Networking, Data Import/Export, Microsoft Excel, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    98K reviews

    Beginner · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    M

    Microsoft

    Microsoft Power BI Data Analyst

    Skills you'll gain: Power BI, Microsoft Excel, Data Analysis, Microsoft Power Platform, Data Integrity, Data Visualization, Data Storage, Data Collection, Data Quality, Data Manipulation, Business Analytics, Timelines, Advanced Analytics, Database Design, Statistical Reporting, Report Writing, Data Processing, Data Warehousing, Business Intelligence, SQL

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    9K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • The Google AI Certificate that powers your career

    Enroll now
  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    LLM Optimization & Evaluation

    Skills you'll gain: Apache Airflow, MLOps (Machine Learning Operations), User Acceptance Testing (UAT), Prompt Patterns, LLM Application, AI Security, Extract, Transform, Load, Scripting, Technical Communication, SQL, Data Pipelines, PyTorch (Machine Learning Library), Miro AI, Data Presentation, Large Language Modeling, Python Programming, Performance Tuning, Root Cause Analysis, Statistical Analysis, Version Control

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Data Engineering

    Skills you'll gain: Data Store, Extract, Transform, Load, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Apache Hadoop, Relational Databases, Apache Spark, Data Lakes, Databases, SQL, NoSQL, Data Security, Data Science

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.6K reviews

    Beginner · Course · 1 - 4 Weeks

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

    IBM

    IBM Data Engineering

    Skills you'll gain: Extract, Transform, Load, NoSQL, Apache Spark, Data Warehousing, Web Scraping, Database Design, Database Administration, Apache Hadoop, Relational Databases, Linux Commands, Data Pipelines, SQL, IBM Cognos Analytics, Data Store, Generative AI, Professional Networking, Data Import/Export, Python Programming, Data Analysis, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    62K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    SQL for Data Science with R

    Skills you'll gain: Database Design, Relational Databases, SQL, Databases, R Programming, Database Management, Data Science, Data Modeling, Query Languages, Data Access, Data Manipulation, Data Analysis

    4.4
    Rating, 4.4 out of 5 stars
    ·
    191 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Python for Everybody

    Skills you'll gain: Database Design, Data Processing, Web Scraping, Data Visualization, Relational Databases, Restful API, Web Services, SQL, Databases, Data Visualization Software, JSON, Interactive Data Visualization, Extensible Markup Language (XML), Data Structures, Programming Principles, Data Cleansing, Network Protocols, Data Analysis, Python Programming, Computer Programming

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    280K reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

1234…47

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

  • IBM Data Science: IBM
  • Databases and SQL for Data Science with Python: IBM
  • Introduction to Data Science: IBM
  • SQL for Data Science: University of California, Davis
  • Data Science Fundamentals with Python and SQL: IBM
  • IBM Data Analyst: IBM
  • Microsoft Power BI Data Analyst: Microsoft
  • LLM Optimization & Evaluation: Coursera
  • Introduction to Data Engineering: IBM
  • IBM Data Engineering: 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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