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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), Keras (Neural Network Library), Deep Learning, Convolutional Neural Networks, Reinforcement Learning, Model Optimization, Autoencoders, Generative AI, Artificial Neural Networks, Transfer Learning, Unsupervised Learning, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Fine-tuning, Generative Model Architectures, Applied Machine Learning, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Logistic Regression

    4.5
    Rating, 4.5 out of 5 stars
    ·
    4.2K 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

  • C

    Coursera

    Basic Image Classification with TensorFlow

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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    848 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Support Vector Machines in Python, From Start to Finish

    Skills you'll gain: Scikit Learn (Machine Learning Library), Predictive Modeling, Tensorflow, Cloud Computing, Statistical Machine Learning, Machine Learning Software, Classification Algorithms, Applied Machine Learning, Machine Learning Methods, Python Programming, Model Training, Data Preprocessing, Data Science, Machine Learning, Model Evaluation, Model Optimization, Scientific Visualization

    4.6
    Rating, 4.6 out of 5 stars
    ·
    162 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • 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

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

  • C

    Coursera

    Medical Insurance Premium Prediction with Machine Learning

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

    4.7
    Rating, 4.7 out of 5 stars
    ·
    27 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    Visualizing Filters of a CNN using TensorFlow

    Skills you'll gain: Tensorflow, Convolutional Neural Networks, Applied Machine Learning, 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

  • 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
    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, Hugging Face, Natural Language Processing, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), 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

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Transformers Unleashed: Master the Architecture of Modern AI

    Skills you'll gain: Model Optimization, MLOps (Machine Learning Operations), Systems Architecture, Model Evaluation, Feature Engineering, AI Integrations, Image Analysis, Model Training, Model Deployment, Extract, Transform, Load, Systems Design, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Apache Spark, Natural Language Processing, Pandas (Python Package), Cloud Deployment, Machine Learning, Computer Vision, Computational Thinking

    Intermediate · Professional Certificate · 3 - 6 Months

1234…20

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
  • Basic Image Classification with TensorFlow: Coursera
  • Support Vector Machines in Python, From Start to Finish: Coursera
  • Creating Multi Task Models With Keras: Coursera
  • Tweet Emotion Recognition with TensorFlow: Coursera
  • Optimize TensorFlow Models For Deployment with TensorRT: Coursera
  • Medical Insurance Premium Prediction with Machine Learning: Coursera
  • Visualizing Filters of a CNN using TensorFlow: 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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