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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
    Status: AI skills
    AI skills
    I

    IBM

    IBM Java Developer

    Skills you'll gain: Prompt Engineering, Software Development Life Cycle, Cloud-Native Computing, Software Architecture, Hibernate (Java), Database Design, Responsive Web Design, Docker (Software), Containerization, Git (Version Control System), GitHub, Object Oriented Programming (OOP), Microservices, CI/CD, Restful API, Java Programming, Engineering Software, Version Control, Database Management, Software Design

    4.6
    Rating, 4.6 out of 5 stars
    ·
    7K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    A

    Amazon

    Amazon Junior Software Developer

    Skills you'll gain: Git (Version Control System), Software Development Methodologies, JUnit, Requirements Analysis, Version Control, Application Development, Software Development Life Cycle, SQL, Full-Stack Web Development, Test Driven Development (TDD), Software Development, Restful API, Object Oriented Programming (OOP), Object Oriented Design, Database Management, MySQL, Digital Transformation, Relational Databases, Java Programming, Generative AI

    4.4
    Rating, 4.4 out of 5 stars
    ·
    493 reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free
    Free
    P

    Princeton University

    Algorithms, Part I

    Skills you'll gain: Data Structures, Algorithms, Java, Performance Testing, Computer Programming, Java Programming, Theoretical Computer Science, Object Oriented Programming (OOP)

    4.9
    Rating, 4.9 out of 5 stars
    ·
    12K reviews

    Intermediate · Course · 3 - 6 Months

  • C

    Coursera

    Introduction to Java Programming: Java Fundamental Concepts

    Skills you'll gain: Java Programming, Java, Integrated Development Environments, Mobile Development, Computer Programming, Object Oriented Programming (OOP), Debugging, Data Structures

    4.4
    Rating, 4.4 out of 5 stars
    ·
    177 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    W

    Whizlabs

    Exam Prep: Oracle Certified Associate, Java SE 8 [1Z0-808]

    Skills you'll gain: Java Programming, Java, Object Oriented Programming (OOP), Oracle SQL Developer, Oracle Databases

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Java Programming and Software Engineering Fundamentals

    Skills you'll gain: Java Programming, Software Design, Debugging, Software Engineering, Javascript, Computer Programming, Event-Driven Programming, Encryption, Algorithms, Image Analysis, Web Applications, Data Processing, Statistical Analysis, Data Import/Export, Predictive Modeling, Integrated Development Environments, Data Manipulation, Data Analysis, Web Servers, Cascading Style Sheets (CSS)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    22K reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Master Java Spring Framework: Build Web Apps

    Skills you'll gain: Object-Relational Mapping, Spring Framework, Hibernate (Java), Apache Maven, Model View Controller, Relational Databases, Database Design, MySQL, Web Applications, Java Platform Enterprise Edition (J2EE), Java Programming, Java, Full-Stack Web Development, Database Application, Database Development, Authentications, Object Oriented Design, Back-End Web Development, Object Oriented Programming (OOP), Software Design Patterns

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D
    U

    Multiple educators

    Object Oriented Programming in Java

    Skills you'll gain: Unit Testing, Data Structures, Event-Driven Programming, Interactive Data Visualization, Java, Java Programming, User Interface (UI), Object Oriented Programming (OOP), Debugging, Object Oriented Design, Computer Programming, Cryptography, Software Engineering, Performance Tuning, Encryption, Algorithms, Programming Principles, Data Analysis, Software Design, Problem Solving

    4.6
    Rating, 4.6 out of 5 stars
    ·
    15K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    B

    Board Infinity

    Java FullStack Developer

    Skills you'll gain: Angular, HTML and CSS, Data Structures, Spring Boot, Eclipse (Software), Restful API, Java Programming, JavaScript Frameworks, Object Oriented Programming (OOP), Model View Controller, Hypertext Markup Language (HTML), Java, Front-End Web Development, Spring Framework, Object Oriented Design, Web Services, Integrated Development Environments, Software Design Patterns, Cascading Style Sheets (CSS), Javascript

    4.4
    Rating, 4.4 out of 5 stars
    ·
    816 reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free
    Free
    P

    Princeton University

    Computer Science: Programming with a Purpose

    Skills you'll gain: Programming Principles, Computer Programming, Object Oriented Programming (OOP), Performance Tuning, Data Structures, Java Programming, Java, Computational Thinking, Computer Science, Algorithms, Animations, Simulations, Debugging

    4.7
    Rating, 4.7 out of 5 stars
    ·
    1.3K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free
    Free
    P

    Princeton University

    Computer Science: Algorithms, Theory, and Machines

    Skills you'll gain: Theoretical Computer Science, Data Structures, Computer Science, Computer Architecture, Algorithms, Programming Principles, Computational Logic, Computational Thinking, Java Programming, Computer Hardware

    4.7
    Rating, 4.7 out of 5 stars
    ·
    739 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Java Spring: Build a Shopping Cart App

    Skills you'll gain: Object-Relational Mapping, Hibernate (Java), Apache Maven, Model View Controller, Spring Framework, Relational Databases, Database Design, MySQL, Java, Java Programming, Full-Stack Web Development, Database Application, Database Development, Authentications, Web Applications, Back-End Web Development, Data Validation, Data Modeling

    Mixed · Course · 1 - 4 Weeks

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

  • IBM Java Developer: IBM
  • Amazon Junior Software Developer: Amazon
  • Algorithms, Part I: Princeton University
  • Introduction to Java Programming: Java Fundamental Concepts: Coursera
  • Exam Prep: Oracle Certified Associate, Java SE 8 [1Z0-808]: Whizlabs
  • Java Programming and Software Engineering Fundamentals: Duke University
  • Master Java Spring Framework: Build Web Apps: EDUCBA
  • Object Oriented Programming in Java: Duke University
  • Java FullStack Developer: Board Infinity
  • Computer Science: Programming with a Purpose: Princeton University

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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