Dr Adrian Bevan, a former course leader, discusses the Practical Machine Learning course
Academic Lead: Dr Dimitris Kalogiros
Machine learning influences modern life in many different avenues and is silently revolutionising the way we live and work. We can see the influence of machine-learning algorithms in social media, web search engines, mobile device spell checkers and self-driving cars. This course will give you an introduction to machine learning using the Python programming language and the TensorFlowTM programming toolkit from Google. No programming background is assumed, however if you want to take this course, you should be familiar with using computers.
This course is taught by scientists using machine learning for data analysis at CERN’s Large Hadron Collider and will allow you to work on practical examples from both general and physics-based problems. Examples will be drawn from a variety of problems in order to allow you to build up an understanding of the tools and how to use them. This will prepare you for a mini-project analysing data from a particle physics experiment to complement the examples encountered earlier in the course.
Course content is subject to change.
This is a practical course that provides you with an introduction to the concepts of machine learning and the application of algorithms to several types of available data samples. In order to achieve this, you will be introduced to the Python programming language and key concepts related to the TensorFlowTM programming toolkit. You will learn how to train machine-learning algorithms and evaluate their performance on image data and scientific data from the Large Hadron Collider. We will develop your programming skills so that you can explore the potential benefits of deep-learning algorithms.
You will be taught through a combination of lectures, laboratory work, and workshops.
You will learn/develop:
You will develop/be able to:
Additional costs
All reading material will be provided online, so it is not necessary to purchase any books.
For course and housing fees visit our finance webpage
We welcome Summer School students from around the world. We accept a range of qualifications
Have a question? Get in touch - one of the team will be happy to help!
Applications close 24 May 2024
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