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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
    M

    Microsoft

    Microsoft Azure Data Scientist Associate (DP-100) Exam Prep

    Skills you'll gain: Responsible AI, Model Deployment, Convolutional Neural Networks, Classification Algorithms, Data Analysis, Image Analysis, Model Evaluation, Transfer Learning, Data Ethics, Machine Learning, Tensorflow, Data Processing, Data Pipelines, Data Transformation, Data Preprocessing, Machine Learning Software, Distributed Computing, Information Privacy, Supervised Learning, Virtual Machines

    4.2
    Rating, 4.2 out of 5 stars
    ·
    607 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Enterprise Workflow

    Skills you'll gain: Feature Engineering, Model Deployment, Data Visualization, Data Ethics, Exploratory Data Analysis, Model Evaluation, Unsupervised Learning, Data Presentation, Tensorflow, Dimensionality Reduction, MLOps (Machine Learning Operations), Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Data Science, Machine Learning, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    353 reviews

    Advanced · Specialization · 3 - 6 Months

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

    IBM

    IBM Deep Learning with PyTorch, Keras and Tensorflow

    Skills you'll gain: Transfer Learning, PyTorch (Machine Learning Library), Model Evaluation, Vision Transformer (ViT), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Convolutional Neural Networks, Unsupervised Learning, Autoencoders, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Logistic Regression, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Image Analysis, Data Preprocessing, Model Deployment

    4.5
    Rating, 4.5 out of 5 stars
    ·
    4.1K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D
    S

    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
    ·
    38K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Preparing for Google Cloud Certification: Cloud Data Engr

    Skills you'll gain: Real Time Data, Data Lakes, Model Deployment, Google Cloud Platform, Feature Engineering, PySpark, Data Pipelines, Cloud Storage, Data Import/Export, Dataflow, Big Data, Apache Spark, Apache Hadoop, Dashboard, Data Architecture, Data Governance, Apache Kafka, Data Infrastructure, Tensorflow, Data Warehousing

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.9K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    DevOps, DataOps, MLOps

    Skills you'll gain: MLOps (Machine Learning Operations), Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Containerization, Tensorflow, Rust (Programming Language), Microsoft Copilot, DevOps, Hugging Face, Applied Machine Learning, Cloud Solutions, CI/CD, Machine Learning, Serverless Computing, Docker (Software), GitHub, Big Data

    4.2
    Rating, 4.2 out of 5 stars
    ·
    209 reviews

    Advanced · Course · 1 - 3 Months

What brings you to Coursera today?

  • C

    Coursera

    Basic Image Classification with TensorFlow

    Skills you'll gain: Model Evaluation, Keras (Neural Network Library), Tensorflow, Image Analysis, Artificial Neural Networks, Deep Learning, Computer Vision, Machine Learning, Classification Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    847 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Next level skills. New Year savings.

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  • C

    Coursera

    Tweet Emotion Recognition with TensorFlow

    Skills you'll gain: Recurrent Neural Networks (RNNs), Tensorflow, Python Programming, Natural Language Processing, Data Preprocessing, Applied Machine Learning, Text Mining, Machine Learning Algorithms, Deep Learning, Classification Algorithms, Machine Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    173 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Medical Insurance Premium Prediction with Machine Learning

    Skills you'll gain: Data Visualization, Keras (Neural Network Library), Data Preprocessing, Artificial Neural Networks, Interactive Data Visualization, Predictive Modeling, Tensorflow, Applied Machine Learning, Feature Engineering, Data Science, Predictive Analytics, Data Manipulation, Machine Learning, Model Evaluation, Regression Analysis, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    26 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Transfer Learning for NLP with TensorFlow Hub

    Skills you'll gain: Transfer Learning, Tensorflow, Natural Language Processing, Keras (Neural Network Library), Embeddings, Deep Learning, Classification Algorithms, Model Evaluation, Machine Learning, Software Visualization

    4.8
    Rating, 4.8 out of 5 stars
    ·
    181 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Preview
    Preview
    O

    O.P. Jindal Global University

    Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Scikit Learn (Machine Learning Library), Tensorflow, Applied Machine Learning, Artificial Neural Networks, Python Programming, NumPy, Matplotlib, Deep Learning, Image Analysis, Machine Learning, Embeddings, Pandas (Python Package), Convolutional Neural Networks, Natural Language Processing, Regression Analysis

    Build toward a degree

    3.6
    Rating, 3.6 out of 5 stars
    ·
    7 reviews

    Beginner · Course · 1 - 3 Months

  • C

    Coursera

    Visualizing Filters of a CNN using TensorFlow

    Skills you'll gain: Tensorflow, Convolutional Neural Networks, Image Analysis, Python Programming, Jupyter, Artificial Neural Networks, Deep Learning, Software Visualization, Machine Learning

    4.4
    Rating, 4.4 out of 5 stars
    ·
    84 reviews

    Intermediate · Guided Project · Less Than 2 Hours

What brings you to Coursera today?

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

  • Microsoft Azure Data Scientist Associate (DP-100) Exam Prep: Microsoft
  • IBM AI Enterprise Workflow: IBM
  • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
  • Machine Learning: DeepLearning.AI
  • Preparing for Google Cloud Certification: Cloud Data Engr: Google Cloud
  • DevOps, DataOps, MLOps: Duke University
  • Basic Image Classification with TensorFlow: Coursera
  • Tweet Emotion Recognition with TensorFlow: Coursera
  • Medical Insurance Premium Prediction with Machine Learning: Coursera
  • Transfer Learning for NLP with TensorFlow Hub: Coursera

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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