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> Study at Esisar > Engineering degree in Information Technology & Security

Machine learning - 5AMCS529

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  • Number of hours

    • Lectures : 15.0
    • Tutorials : -
    • Laboratory works : 6.0
    • Projects : -
    • Internship : -
    • Written tests : -
    ECTS : 3.5
  • Officials : Laurent LEFEVRE

Goals

Investigate the main models of Artificial Intelligence. The courses and practical work allow students to discover and create AI models by themselves, starting from elementary components (such as the formal neuron) towards the most complex models (such as deep neural networks). Unlike black-box approach, the course aims at understanding in detail how the models studied work.

Content

  • The history of AI and its various models
  • neural networks: from formal neuron to deep learning
  • unsupervised networks and self-organizing maps
  • reinforcement learning
  • robotics and developmental learning

Prerequisites

A preliminary experience (basic knowledge) in programming (Java and Python)

Tests

The evaluation includes two labs (50%) and a final exam (50%).
TP (lab): two sessions with evaluation of in-session work and written report
E1: session 1 individual exam (practical and theoretical)
E2: session 2 individual exam (practical and theoretical)
DM: (in case of confinment) individual homework with report and online oral exam

The exam is given in english only FR

Calendar

The course exists in the following branches:

see the course schedule for 2022-2023

Additional Information

Course ID : 5AMCS529
Course language(s): FR

The course is attached to the following structures:

You can find this course among all other courses.

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Date of update October 29, 2021

Université Grenoble Alpes