LEVEL
Practical

DURATION
8 hours

TRAINER
CIM4.0

PRICE

Description

Computer Vision: from theory to training on real data.
A practical module to learn how Computer Vision works and how to use neural network-based models to analyze, classify, and interpret visual content. From pre-processing to CNNs to real-world examples such as object and scene recognition on industrial datasets.
You can take this module individually or join the full AI practical course.

Macro Topics

Introduction to Computer Vision

• Image acquisition and pre-processing
• Feature extraction and image classification (openCV)

Convolutional neural networks

• Architecture and operation of CNNs
• Application of CNNs for image classification

Practical exercises

• Object recognition in images with a pre-trained CNN (YOLO)
• Examples of training a neural network on a custom dataset (Stellantis DPI)
• Watching Roboflow for (almost) instant training

Implementation of a prediction system on the jersey of a player of
soccer

Trainee’s Profile

The course is aimed at developers, software engineers and technical

Pre-Requirements

Knowledge of basic Python and theoretical knowledge of AI

Objectives

At the end of the module, participants will be able to apply artificial intelligence to image and video analysis in real-world contexts.

More info

English language available upon request.
The subscription must be carried out within the fifth working day preceding the course starting date.