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Deep Learning with TensorFlow

Total apprenants : 85

Taux de réussite : 83 %

Discover the advanced technique of Deep Learning and build your own deep neural network to tackle a real world Data Science problem, by using TensorFlow, the most popular Machine Learning library in the world!

AUDIENCE: Anyone with software development bases wishing to develop a new skill.


    Please plan to arrive a few minutes early.
    Please have a computer that you can install software on, with Chrome browser and a Gmail account.
    The next available session (date, time, method of face-to-face participation or webinar) is displayed under the blue button “take this training”.

    If no session is offered, contact us via the page: Contact.
    Beforehand, read the Internal regulations
    If you have any questions, please do not hesitate to contact us by email: info@iamondada.com


    • Being initiated to Deep Learning on a practical case, enhance your profile with a new skill.
    • Have taken your first steps with TensorFlow .


    • Understand the difference between Machine Learning, Deep Learning and Artificial Intelligence (AI).
    • Understand how AI is used today by companies to gain competitiveness.
    • Understand the basic concepts of Machine Learning such as: the perceptron, the neural network and the different hyperparameters of a deep neural network.
    • Discover computer vision and how to implement a simple neural network through a practical case with TensorFlow.


    You must have a basic knowledge of software development, regardless of the language (php, javascript, C, C ++, Java, Python …), and know what a variable, write functions, write loops (for), write conditions (if) and know what an object and a class are.

    Before registering, check that you have the required level, by carrying out the Test accessible on this link


    • This 7-hour course is offered mainly face-to-face in Paris, in the 15th arrondissement (unless otherwise specified), and sometimes in Webinar (to be accessed from the Chrome browser).
    • Face-to-face, training generally takes place on Saturdays from 9 a.m. to 6 p.m. with breaks, including one for lunch, which is not provided.
    • To ensure the active participation of everyone, the number of places is limited to 12 people per session.
    • The next available session (date, time, method of face-to-face participation or webinar) is displayed under the blue button “take this training”. If no session is offered, contact us via the page: Contact.
    • Please plan to arrive a few minutes early. Practical access information will be communicated to you on this page, after your registration.
    • For the practical case, equip yourself with:
      • a computer on which you can install software
      • the Chrome browser
      • a Gmail account, essential to access certain Google Cloud tools
    • Before registering, if you wish to discuss your training needs, please formulate them from form accessible from this link
    • For any request for information, especially for people with disabilities, please consult us via the page: Contact.


    • Introduction to artificial intelligence (AI)
      • What is artificial intelligence?
      • AI, Machine Learning, Deep Learning and Data Science.
      • Why use AI and how does it work?
    • Presentation of use cases of Deep Learning
      • The classification of cucumbers.
      • The autonomous car.
      • Automatic detection of cancer.
      • Automatic theft detection.
    • Basic concepts of Deep Learning
      • Regression and classification.
      • The perceptron and neural networks.
      • Forward propagation, backpropagation, error function and gradient descent
      • The hyper-parameters of a Deep Learning model.
      • Play with a neural network on TensorFlow Playground.
    • Practical case “La Poste” with TensorFlow

      Build software that can recognize handwritten numbers!

      Handwriting recognition is a recurring problem for La Poste, the banking industry and any company that needs to analyze handwritten documents. Your challenge is to use Deep Learning to develop an AI capable of recognizing handwritten numbers from an image!

      You can use the completed project to present it in your portfolio.

    • Self-assessment quiz of the knowledge acquired to obtain your training certificate.
    • Thoughts on how to go further.


    This training was co-designed by Camilo Rodriguez (trainer in schools of engineers, consultant and developer in Artificial Intelligence) and Hamed Zitoun (Data Scientist and Machine Learning Engineer).

    Course Curriculum

    Student profile Unlimited
    Quiz Deep Learning with TensorFlow 00:00:00
    Training material Deep Learning with Tensorflow 00:00:00

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