Deep learning

Part-Time

Learn how to perfectly manipulate Keras and TensorFlow tools Improve your programming skills Master artificial intelligence techniques such as Computer Vision and Natural Language Processing

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Upcoming Dates

October 01, 2024

November 05, 2024

December 03, 2024

Certified Courses

Training content (280 hours total)

Keras
Convolutional Neural Networks

TensorFlow
Application to speech recognition

Preprocessing and feature engineering
Regression and classification of time series

Deep Learning for face detection

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Throughout your Deep learning training, you will carry out a 120-hour project.
The objective: apply what you’ve learned to a real project (which you can choose!) and benefit from a first concrete experience to add to your portfolio.

This course includes an AWS Cloud Practioner course leading to an official AWS certification.

METHODOLOGY

Hybrid learning format

Combining flexible learning on a platform and Masterclasses led by a Data Engineer. It's the combination that has won over more than 15,000 alumni, giving our courses a completion rate of +98%!

Our teaching method is based on learning by doing:

Practical application: All our training modules include online exercises so that you can apply the concepts developed in the course.
Masterclass: For each module, 1 or 2 Masterclasses are organised live with a trainer to address current issues in technologies, methods and tools in the field.

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Training objectives

Deep Learning fundamentals

Use the Keras and Tensorflow libraries to pre-process and augment data, and design and optimize an artificial intelligence solution.
Transform data to make it usable in terms of form and content.
Identify the main features of a neural network based on a structured dataset or images.

Computer Vision

Analyze the relevant data to be integrated into the artificial intelligence solution
Transform data to make it usable in terms of form and content
Develop an artificial intelligence solution applied to computer vision to reproduce human vision capable of processing and understanding image content
Evaluate and interpret results

Natural Language Processing

Analyze relevant data for integration into the artificial intelligence solution
Extract and transform data to make it usable
Develop an artificial intelligence solution applied to natural language processing
Evaluate and interpret results