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Event — December 02 to 03, 2020

Introduction to Machine Learning and Deep Learning

Time 9:00

Venue Online

Upon completion of this course, participants will be able to apply techniques and principles related to artificial intelligence (Machine Learning and Deep Learning) to their corporate projects.

Objectives
Upon completion of this course, participants will be able to apply techniques and principles related to artificial intelligence (Machine Learning and Deep Learning) to their corporate projects.


Targeted audience
Programmers, programmer analysts, IT project managers, IT directors


Prerequisite
Participants must be able to draw upon basic programming and mathematical notions (linear algebra, statistical probabilities). Basic knowledge of the Python programming language and the Jupyter environment is an asset.

Training detail

  • Basics of machine learning At the end of this unit, participants will be able to provide a brief summary of the basic components of an AI problem.
  • Automatic learning algorithms At the end of this unit, participants will be able to describe the key AI algorithms used to resolve simple problems.
  • Different steps of a corporate AI project At the end of this unit, participants will be able to describe the main steps of a corporate AI project.
  • Introduction to neural networks At the end of this unit, participants will be able to describe the characteristics of deep learning
  • Recurrent and convolutional neural networks At the end of this unit, participants will be able to describe the characteristics of recurrent and convolutional neural networks.
  • Launch of AI and its implications At the end of this unit, participants will be aware of the risks associated with inexperienced or fraudulent use of artificial intelligence