• University of York
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Intelligent Systems: An Introduction to Deep Learning and Autonomous Systems

Discover the benefits and risks of deep learning and its uses in systems such as assistive technology and facial recognition.

605 enrolled on this course

Intelligent Systems: An Introduction to Deep Learning and Autonomous Systems

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.

On 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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Skip to 0 minutes and 6 seconds From Ada Lovelace’s pioneering work in the 1840s 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. This allows us to solve problems that were previously too complex for humans to code. Our researchers here in the Department of Computer Science at the University of York are pushing the boundaries in machine learning for computer vision, natural language processing and robotics. They are also developing new ways to verify the safety and security of autonomous systems whose software relies on machine learning.

Skip to 0 minutes and 58 seconds These technologies will have a direct impact on the way we lead our lives in the future. In this course, we will introduce you to deep learning, a form of machine learning that has provided performance breakthroughs across a whole host of areas. As well as fundamental theory and techniques, you will see how it can be used in applications such as face recognition, self-driving cars and robotics. We will also consider ethical implications such as learning from personal or biased data and trusting your safety to a learnt system that no human can understand. Join us for a journey into the world of deep learning and gain an insight into tomorrow’s intelligent systems.

What topics will you cover?

  • 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

When would you like to start?

Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

Learning on this course

You can take this self-guided course and learn at your own pace. On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Describe the differences between machine learning and conventional programming
  • Investigate the classification of images through deep learning
  • Identify the social and medical benefits of assistive technology
  • Reflect upon the ways data is collected and processed in autonomous vehicles
  • Discuss the ethical issues surrounding autonomous vehicles

Who is the course for?

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).

Who will you learn with?

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

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

I am a lecturer at the Department of Computer Science, University of York.

I'm a Lecturer in System Safety Engineering at the University of York. My research looks at how humans can contribute to the safety - or the un-safety - of systems, and at risk communication.

Who developed the course?

University of York

The University of York combines the pursuit of academic excellence with a culture of inclusion, which encourages everyone – from a variety of backgrounds – to achieve their best.

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Available until 22 November 2021 at 23:59 (UTC). T&Cs apply.

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