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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 Deep Learning with PyTorch, Keras and Tensorflow

    Skills you'll gain: PyTorch (Machine Learning Library), Model Optimization, Keras (Neural Network Library), Deep Learning, Convolutional Neural Networks, Reinforcement Learning, Transfer Learning, Autoencoders, Generative AI, Unsupervised Learning, Tensorflow, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Generative Model Architectures, Model Training, Logistic Regression, Image Analysis, Applied Machine Learning, Regression Analysis

    4.5
    Rating, 4.5 out of 5 stars
    ·
    4.3K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Advanced Machine Learning on Google Cloud

    Skills you'll gain: Model Deployment, Model Optimization, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Model Training, Transfer Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Machine Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free
    Free
    C

    Coursera

    Creating Multi Task Models With Keras

    Skills you'll gain: Keras (Neural Network Library), Tensorflow, Model Training, Applied Machine Learning, Convolutional Neural Networks, Deep Learning, Model Optimization, Machine Learning, Computer Vision

    4.7
    Rating, 4.7 out of 5 stars
    ·
    78 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    Tweet Emotion Recognition with TensorFlow

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

    4.5
    Rating, 4.5 out of 5 stars
    ·
    174 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    Object Localization with TensorFlow

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

    4.3
    Rating, 4.3 out of 5 stars
    ·
    117 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • G

    Google Cloud

    Learning TensorFlow: the Hello World of Machine Learning

    Skills you'll gain: Tensorflow, Google Cloud Platform, Scripting, Data-Driven Decision-Making, Model Training, Applied Machine Learning, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Development Environment

    4
    Rating, 4 out of 5 stars
    ·
    20 reviews

    Beginner · Project · Less Than 2 Hours

What brings you to Coursera today?

  • Status: Free
    Free
    C

    Coursera

    Optimize TensorFlow Models For Deployment with TensorRT

    Skills you'll gain: Keras (Neural Network Library), Model Optimization, Tensorflow, Deep Learning, Performance Tuning, Model Deployment, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    77 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    Transfer Learning for NLP with TensorFlow Hub

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

    4.8
    Rating, 4.8 out of 5 stars
    ·
    182 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Data Balancing with Gen AI: Credit Card Fraud Detection

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Fraud detection, Generative Model Architectures, Keras (Neural Network Library), Tensorflow, Data Preprocessing, Deep Learning, Dimensionality Reduction, Data Visualization, Model Training, Data Synthesis, Python Programming

    4.1
    Rating, 4.1 out of 5 stars
    ·
    9 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    Create a Superhero Name Generator with TensorFlow

    Skills you'll gain: Tensorflow, Natural Language Processing, Python Programming, Applied Machine Learning, Machine Learning Methods, Model Training, Recurrent Neural Networks (RNNs), Generative Model Architectures, Machine Learning, Deep Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    38 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Preparing for Google Cloud Certification: Cloud Data Engr

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

    DeepLearning.AI

    Deep Learning

    Skills you'll gain: Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Computer Vision, Transfer Learning, Deep Learning, Image Analysis, Model Optimization, Artificial Intelligence and Machine Learning (AI/ML), Hugging Face, Natural Language Processing, Artificial Neural Networks, Tensorflow, Applied Machine Learning, Model Training, Fine-tuning, Generative AI, Embeddings, Supervised Learning, Large Language Modeling, Artificial Intelligence

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    147K reviews

    Intermediate · Specialization · 3 - 6 Months

1234…19

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

  • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
  • Advanced Machine Learning on Google Cloud: Google Cloud
  • Creating Multi Task Models With Keras: Coursera
  • Tweet Emotion Recognition with TensorFlow: Coursera
  • Object Localization with TensorFlow: Coursera
  • Learning TensorFlow: the Hello World of Machine Learning: Google Cloud
  • Optimize TensorFlow Models For Deployment with TensorRT: Coursera
  • Transfer Learning for NLP with TensorFlow Hub: Coursera
  • Data Balancing with Gen AI: Credit Card Fraud Detection: Coursera
  • Create a Superhero Name Generator with TensorFlow: 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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