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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
    D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Exploratory Data Analysis, Statistical Hypothesis Testing, Sampling (Statistics), Probability & Statistics, Linear Algebra, Bayesian Statistics, Probability Distribution, Statistical Machine Learning, Data Science, Probability, NumPy, Applied Mathematics, Dimensionality Reduction, Data Transformation, Calculus, Numerical Analysis, Machine Learning Algorithms, Machine Learning, Data Manipulation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.1K reviews

    Intermediate · Specialization · 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
    ·
    786 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Linear Algebra, Dimensionality Reduction, Regression Analysis, NumPy, Calculus, Applied Mathematics, Probability & Statistics, Artificial Neural Networks, Data Preprocessing, Statistical Analysis, Unsupervised Learning, Advanced Mathematics, Jupyter, Statistics, Machine Learning Algorithms, Algorithms, Python Programming, Machine Learning, Derivatives

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

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Mathematical Foundations for Data Science and Analytics

    Skills you'll gain: Probability Distribution, Statistical Analysis, NumPy, Matplotlib, Probability & Statistics, Regression Analysis, Data Science, Pandas (Python Package), Probability, Statistical Modeling, Predictive Modeling, Linear Algebra, Data Analysis, Statistical Methods, Predictive Analytics, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning

    Build toward a degree

    4.1
    Rating, 4.1 out of 5 stars
    ·
    7 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Linear Algebra for Machine Learning and Data Science

    Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Data Transformation, Data Manipulation, Algebra, Advanced Mathematics, Jupyter, Applied Mathematics, Python Programming, Machine Learning, Debugging

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • I

    IIT Guwahati

    Bachelor of Science in Data Science & AI

    Skills you'll gain: Package and Software Management, Time Series Analysis and Forecasting, Cloud Computing Architecture, Linear Algebra, Data Structures, Data Warehousing, Data Visualization, Model Evaluation, Database Management, Database Theory, Social Network Analysis, Algorithms, Deep Learning, Portfolio Management, Oral Comprehension, Java Programming, C (Programming Language), Object Oriented Programming (OOP), Spreadsheet Software, Econometrics

    Earn a degree

    Degree · 1 - 4 Years

What brings you to Coursera today?

  • 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, Design Strategies, Pseudocode, Computer Science, Program Development, Tree Maps, Encryption, Linear Algebra, Combinatorics, Mathematical Theory & Analysis, Data Science, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    912 reviews

    Advanced · Specialization · 3 - 6 Months

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • U

    University of Huddersfield

    BSc Data Science

    Skills you'll gain: Linear Algebra, Matplotlib, Computational Logic, Theoretical Computer Science, Graph Theory, Data Visualization Software, Algebra, Python Programming, Data Analysis, Computational Thinking, Algorithms, Logical Reasoning, Data Manipulation, Statistical Analysis, Data Structures, Data Science, Computer Science, Advanced Mathematics, Numerical Analysis, Applied Mathematics

    Earn a degree

    Degree · 1 - 4 Years

  • Status: Preview
    Preview
    U

    University of Washington

    Computational Neuroscience

    Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Bioinformatics, Mathematical Modeling, Physiology, Recurrent Neural Networks (RNNs), Biology, Linear Algebra, Statistical Methods, Information Architecture, Differential Equations, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.1K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Linear Models for Data Science 2: Statistical Linear Models

    Skills you'll gain: Regression Analysis, Linear Algebra, R Programming, Data Science, Probability Distribution, Statistical Modeling, Mathematical Modeling, Probability & Statistics, Applied Mathematics, Statistical Analysis, Statistical Inference

    4.6
    Rating, 4.6 out of 5 stars
    ·
    106 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    H

    Howard University

    Introduction to Linear Algebra and Python

    Skills you'll gain: Linear Algebra, Data Visualization, Applied Mathematics, NumPy, Jupyter, Mathematical Modeling, Data Science, Python Programming, Software Installation, Data Manipulation, Git (Version Control System)

    4.4
    Rating, 4.4 out of 5 stars
    ·
    16 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Expressway to Data Science: Essential Math

    Skills you'll gain: Linear Algebra, Integral Calculus, Algebra, Numerical Analysis, Calculus, Graphing, Applied Mathematics, Data Science, Mathematical Theory & Analysis, Data Analysis, Statistical Methods, Derivatives

    4.5
    Rating, 4.5 out of 5 stars
    ·
    474 reviews

    Intermediate · 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

  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Advanced Statistics for Data Science: Johns Hopkins University
  • Mathematics for Machine Learning: Imperial College London
  • Mathematical Foundations for Data Science and Analytics: University of Pittsburgh
  • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
  • Bachelor of Science in Data Science & AI: IIT Guwahati
  • Foundations of Data Structures and Algorithms: University of Colorado Boulder
  • BSc Data Science: University of Huddersfield
  • Computational Neuroscience: University of Washington
  • Advanced Linear Models for Data Science 2: Statistical Linear Models: Johns Hopkins 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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