IA102

Introduction to Machine Learning and Deep Learning

  • Duration 2 DAYS
  • Regular fee 1 000
  • Preferential fee 900?
  • Locations
    • Montreal
  • New course
SUMMARY
DETAILS

Objectives

To provide the knowledge and skills required to understand and support decision making related to Machine Learning and Deep Learning projects.

Targeted audience

Account or project managers, directors, stakeholders, IT managers, analysts, CFOs and accountants.

Prerequisite

None.

Content

  • Introduction to Artificial Intelligence and its role in modern IT
  • Fundamentals: neural networks, examples of convolutional and recurrent networks
  • Machine learning: the principles of learning and key concepts—data, learning concepts, predictions on new data
  • Data to rely on: internal company data, data acquired externally
  • Supervised, unsupervised, adaptive and reinforcement training
  • Linear models of learning: regression, logistic, predictive (Bayesien, decision trees…)
  • Tools for implementation: API, languages, local and Cloud platforms
  • Examples of how machine learning is used: decisions, image recognition, natural language processing
  • The special case of deep learning, algorithms and API, applications
  • Implementing a learning project or deep learning project, required skills, industries

DATES*

*Unless stated otherwise, all sessions are in French.
  • Montreal

    June 19 to June 20 2019

  • Montreal

    November 11 to November 12 2019

Trainer(s) assigned(s)