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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


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  • 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 Analysis, Data Science, Statistics, Mathematical Modeling, Data Modeling, Applied Mathematics

    4.4 stars, 800 reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.4 (800) · Advanced · Specialization · 3 - 6 Months

    Status: Free trial
    Free trial
  • D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning

    4.6 stars, 3.3K reviews, Intermediate, Specialization, 1 - 3 Months

    ★ 4.6 (3.3K) · Intermediate · Specialization · 1 - 3 Months

    Status: Top AI program
    Top AI program
    Status: Free trial
    Free trial
  • U

    University of Huddersfield

    BSc Data Science

    Skills you'll gain: Data Literacy, Linear Algebra, Graph Theory, Statistical Software, Big Data, Computational Logic, Back-End Web Development, Integral Calculus, Analytics, Matplotlib, Data Visualization, Probability & Statistics, Statistical Programming, Plot (Graphics), Calculus, Scatter Plots, Data Mining, R Programming, Relational Databases, Applied Mathematics

    Degree · 1 - 4 Years

    Category: Job ready
    Job ready
  • U

    University of Pittsburgh

    Mathematical Foundations for Data Science and Analytics

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

    3.6 stars, 16 reviews, Beginner, Specialization, 1 - 3 Months

    ★ 3.6 (16) · Beginner · Specialization · 1 - 3 Months

    Status: Free trial
    Free trial
  • I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Unsupervised Learning, Applied Mathematics, Statistical Methods, Descriptive Statistics, Model Optimization, Mathematical Software, Machine Learning Methods, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Geometry, Artificial Neural Networks, Data Science, Data Manipulation

    4.6 stars, 15K reviews, Beginner, Specialization, 3 - 6 Months

    ★ 4.6 (15K) · Beginner · Specialization · 3 - 6 Months

    Status: Top AI program
    Top AI program
    Status: Free trial
    Free trial

What brings you to Coursera today?

  • I

    Imperial College London

    Mathematics for Machine Learning: Linear Algebra

    Skills you'll gain: Linear Algebra, Applied Mathematics, Jupyter, Data Science, Data Manipulation, Dimensionality Reduction, Data Transformation, Machine Learning, Computational Thinking

    4.6 stars, 13K reviews, Beginner, Course, 1 - 3 Months

    ★ 4.6 (13K) · Beginner · Course · 1 - 3 Months

    Status: Free trial
    Free trial
  • I

    Imperial College London

    Mathematics for Machine Learning: PCA

    Skills you'll gain: Dimensionality Reduction, NumPy, Unsupervised Learning, Statistical Methods, Descriptive Statistics, Jupyter, Statistics, Geometry, Linear Algebra, Data Transformation, Python Programming, Advanced Mathematics, Applied Mathematics, Calculus

    4 stars, 3.2K reviews, Intermediate, Course, 1 - 4 Weeks

    ★ 4 (3.2K) · Intermediate · Course · 1 - 4 Weeks

    Status: Free trial
    Free trial
  • J

    John Wiley & Sons

    Foundations of Data Science and Statistical Methods

    Skills you'll gain: Statistical Methods, Exploratory Data Analysis, Data Quality, Statistics, Data Analysis, Data Science, Statistical Analysis, Probability & Statistics, Data Storage, Data Collection, Data Management, Data Pipelines, Statistical Machine Learning, Data-Driven Decision-Making, Probability Distribution, Machine Learning, Linear Algebra

    Beginner · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free trial
    Free trial
  • P

    Packt

    Data Science with Python

    Skills you'll gain: Plotly, PyTorch (Machine Learning Library), NumPy, Matplotlib, Pandas (Python Package), Plot (Graphics), Data Visualization Software, Interactive Data Visualization, Machine Learning Methods, Python Programming, Applied Machine Learning, Scatter Plots, Numerical Analysis, Data Manipulation, Deep Learning, Image Analysis, Linear Algebra, Data Wrangling

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Status: Free trial
    Free trial
  • J

    Johns Hopkins University

    Differential Calculus through Data and Modeling

    Skills you'll gain: Calculus, Applied Mathematics, Data Modeling, Model Optimization, Estimation, Graphing, Mathematical Modeling, Data Analysis Software, Algebra, Cost Estimation, Mathematical Software, Linear Algebra, Trigonometry, General Mathematics, Advanced Mathematics, Analysis, Derivatives, Mathematical Theory & Analysis, Geometry, Data Analysis

    4.8 stars, 402 reviews, Intermediate, Specialization, 3 - 6 Months

    ★ 4.8 (402) · Intermediate · Specialization · 3 - 6 Months

    Status: Free trial
    Free trial
  • U

    University of Colorado Boulder

    Spacecraft Dynamics and Control

    Skills you'll gain: Control Systems, Mechanics, Torque (Physics), Simulation and Simulation Software, Linear Algebra, Numerical Analysis, Simulations, Engineering Analysis, Automation Engineering, Differential Equations, Trigonometry, Mathematical Modeling, Engineering Calculations, Applied Mathematics, Engineering, Advanced Mathematics, Algorithms, Physics, Calculus

    4.8 stars, 444 reviews, Advanced, Specialization, 3 - 6 Months

    ★ 4.8 (444) · Advanced · Specialization · 3 - 6 Months

    Status: Free trial
    Free trial
  • U

    University of Colorado Boulder

    Integral Calculus and Numerical Analysis for Data Science

    Skills you'll gain: Integral Calculus, Numerical Analysis, Calculus, Data Science, Applied Mathematics, Linear Algebra, Probability & Statistics, Derivatives

    4.6 stars, 111 reviews, Intermediate, Course, 1 - 4 Weeks

    ★ 4.6 (111) · Intermediate · Course · 1 - 4 Weeks

    Status: Free trial
    Free trial

What brings you to Coursera today?

1234…14

Best Data Science courses from Imperial College London

Top-rated Data Science courses offered by Imperial College London on Coursera.

  1. 1
    Mathematics for Machine Learning
    Imperial College LondonBeginner3 - 6 Months4.6(15,097)Imperial College London
  2. 2
    Mathematics for Machine Learning: Linear Algebra
    Imperial College LondonBeginner1 - 3 Months4.6(12,613)Imperial College London
  3. 3
    Mathematics for Machine Learning: PCA
    Imperial College LondonIntermediate1 - 4 Weeks4.0(3,189)Imperial College London

Best Data Science certificate programs

Earn a certificate in Data Science from top universities and companies.

  1. 1
    Advanced Statistics for Data Science
    Johns Hopkins UniversityAdvanced3 - 6 Months4.4(800)Specialization
  2. 2
    Mathematics for Machine Learning and Data Science
    DeepLearning.AIIntermediate1 - 3 Months4.6(3,250)Specialization
  3. 3
    Mathematical Foundations for Data Science and Analytics
    University of PittsburghBeginner1 - 3 Months3.6(16)Specialization

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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