• Length:
    5 Weeks
  • Effort:
    4–6 hours per week
  • Price:

    FREE
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  • Institution
  • Subject:
  • Level:
    Intermediate
  • Language:
    English
  • Video Transcript:
    English

Prerequisites

A minimal knowledge of programming (ideally Python) and basic knowledge in mathematics (linear algebra, statistics) is desirable.

About this course

Skip About this course

Gain a good understanding of what Deep Learning is, what types of problems it resolves and what are the fundamental concepts and methods it entails. The course developed by IVADO, Mila and Université de Montréal uses diversified learning tools in order for you to fully grasp the extent of this ground-breaking cross-cutting technology, a critical need in the field.

IVADO, a scientific and economic data science hub bridging industrial, academic and government partners with expertise in digital intelligence designed the course, and the world-renowned Mila, rallying researchers specialized in Deep Learning, created the content. Mila’s founder and IVADO’s scientific director, Yoshua Bengio, also a professor at Université de Montréal, is a world-leading expert in artificial intelligence and a pioneer in deep learning as well as the scientific director of this course. He is also a joint recipient of the 2018 A.M. Turing Award, “the Nobel Prize of Computing”, for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing.

Deep Learning is an extension of Machine Learning where machines can learn by experience without human intervention. It is largely influenced by the human brain in the fact that algorithms, or artificial neural networks, are able to learn from massive amounts of data and acquire skills that a human brain would. It is now largely used and has considerably improved automation in various fields of our daily lives. Specifically, it transforms the computer vision, speech recognition, and automated translation domains, and it successfully applies to such areas as Economy, Transport, Health, Finance and Energy.

If you are a professional, a scientist or an academic with basic knowledge in mathematics and programming, this MOOC is designed for you! Atop the rich Deep Learning content, discover issues of bias and discrimination in machine learning and benefit from this sociotechnical topic that has proven to be a great eye-opener for many.

What you'll learn

Skip What you'll learn

At the end of the MOOC, participants should be able to:

  • Understand the basics and terminology related to Deep Learning
  • Understand the methodology for carrying out a project in Deep Learning
  • Identify the types of neural networks to use to solve different types of problems
  • Get familiar with Deep Learning libraries through practical and tutorial sessions

MODULE 1 Machine Learning (ML) and experimental protocol

  • Introduction to ML
  • ML Tools

MODULE 2 Bias and discrimination in ML

  • Differences of fairness
  • Fairness in pre- in- and post-processing

MODULE 3 Introduction to Deep Learning

  • Modular approaches
  • Backpropagation
  • Optimization

MODULE 4 Intro to Convolutional Neural Networks (CNN)

  • Introduction to CNN
  • CNN architectures

MODULE 5 Introduction to Recurrent Neural Networks

  • Sequence to sequence models
  • Concepts in natural language processing

Meet your instructors

Mirko Bronzi
Applied Research Scientist
Mila - Applied Research Team
Golnoosh Farnadi
Researcher and Fellow; MOOC Scientific director
Mila, IVADO
Gaétan Marceau Caron
Applied Research Scientist
Mila - Applied Research Team
Jeremy Pinto
Applied Research Scientist
Mila - Applied Research Team

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Frequently asked questions

What is the complete list of speakers for this course?

Mirko BRONZI

Golnoosh FARNADI

Gaétan MARCEAU-CARON

Jeremy PINTO

Who can take this course?

Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.