Intelligent Systems: An Introduction to Deep Learning and Autonomous Systems
link Source : www.futurelearn.com
date_range Débute le 20 septembre 2021
event_note Se termine le 11 octobre 2021
list 3 séquences
assignment Niveau : Introductif
chat_bubble_outline Langue : Anglais
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Les infos clés

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timer 12 heures de cours

En résumé

Delve into the inner workings of deep learning
From Ada Lovelace until the first decade of this century, we have relied on expert computer programmers to design and write software. Now, a whole new branch of computer science called machine learning is allowing computers to create their own software by learning from data.

On this three-week course from the University of York, you’ll discover the fundamental theory and techniques behind deep learning as well as how it’s used in applications.

Explore machine learning applications and the uses of deep learning
Deep learning is a form of machine learning that has provided performance breakthroughs across a whole host of areas.

From household devices to image processing, you’ll dive into the different areas that currently use deep learning as well as looking at how it works and whether we should worry about machines taking over the world.

Assess the safety and ethics surrounding machine learning
With machine learning giving rise to autonomous systems such as self-driving cars, there are many questions about putting our safety in the hands of these machines.

In this course, you’ll consider the ethical implications of machine learning, such as learning from personal or biased data, and of trusting your safety to a learnt system that no human can understand.

Learn from the experts at the University of York
The Department of Computer Science at the University of York is home to world-leading expertise in computer vision, and to the Assuring Autonomy International Programme, at the leading edge of assuring the safety of autonomous systems through machine learning.

With the help and guidance of top educators from the University of York, you’ll explore the main differences between machine learning and conventional programming and how machine learning is evolving autonomous systems.

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Les prérequis

This course is designed for anyone interested in machine learning and looking to further their understanding of recent innovations and research in the area.

It will be especially useful if you are looking to apply to a related undergraduate programme in the near future.

To fully engage with the materials we recommend you have at least some experience of A-Level Maths (or equivalent).

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Le programme

  • Introduction to Machine Learning and Deep Learning
  • Computer Vision using Deep Learning
  • Analysis of faces, people, and activities
  • Autonomous Systems
  • Safety and Ethics of machine learning
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Les intervenants

William Smith
He is a Reader in the Department of Computer Science. I do research and teach in the areas of computer vision, graphics, and machine learning.

Jenn Chubb
Dr. Jenn Chubb is a philosopher and social scientist working on the ethics and impact of science and emerging technologies.

Kofi Appiah
He is a lecturer at the Department of Computer Science, University of York.

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Le concepteur

University of York

L’université d'York est une université pluri-disciplinaire britannique située à York, dans le Nord de l'Angleterre. Fondée en 1963, l'université a acquis une solide réputation académique au cours de son demi-siècle d'existence

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La plateforme

Futurelearn

FutureLearn est une plate-forme d'apprentissage proposant des formations en ligne ouvertes à tous (MOOC)

Fondée en Décembre 2012, la société est entièrement détenue par l'Open University à Milton Keynes, en Angleterre.

Elle est la 1ère plateforme offrant des MOOC au Royaume-Uni, avec à son actif plus d'une cinquantaine d'universités partenaires provenant du Royaume Uni mais aussi du reste du monde.

FutureLearn se différencie également par des partenariats avec des entités non-universitaires comme le British Museum, le British Council, la British Library et la national Film and Television School.

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