Do you want to learn how machines can learn tasks we thought only human brains could perform? Then take this Deep Learning course developed by IVADO, Mila and Université de Montréal: an extensive overview of the essentials of deep learning, this ground-breaking technology already prevalent in our lives and spanning all sectors.
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 offers diversified learning tools 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. Thus, Deep learning is now able to tackle a large variety of tasks that were considered out of reach a few years ago in computer vision, signal processing, natural language processing, robotics, and sequential decision-making. Because of these recent advances, various industries are now deploying deep learning models that impact various economic sectors such as transport, health, finance, energy, as well as our daily life in general.
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.
At the end of the MOOC, participants should be able to:
Mirko Bronzi‘s PhD dealt with extracting and integrating information from different web sources. He is interested in Natural Language Processing for car virtual assistants and on Clinical Language Understanding for doctor/patient interaction.
Golnoosh Farnadi PhD Computer science on user modeling in social media. She is now a Mila researcher working on fairness-aware sequential decision making. She was a visiting scholar at Polytechnique, UCLA, U. Washington and Microsoft research.
Gaétan Marceau Caron joined Mila in 2017. From 2014 to 2016, he was a postdoctoral researcher at INRIA-Saclay. He received a Ph.D. in Computer Science from Paris-Sud XI University in 2014.
Jeremy is an applied research scientist at Mila. He has a BSc in engineering physics at Polytechnique Mtl and holds a MSc in systems design engineering from U Waterloo. He also has experience from implementing machine learning projects in industry.