Deep Learning Demystified: Foundations for Non-Computer Scientist

22 February 2024 to 23 February 2024 - 13:00-17:00

Hicks Building - G34a, University of Sheffield Campus

Twin Karmakharm

All of our events may be recorded and shared via the University of Sheffield Kaltura platform so those who cannot attend may still benefit. We will consider your attendance implict consent to this.

Course Description

“Deep Learning Demystified: Foundations for Non-Computer Scientists” is an accessible and comprehensive course designed to introduce individuals from diverse backgrounds to the fundamental concepts of deep learning. Through clear explanations and real-world examples, participants will gain a solid understanding of key components of deep learning. By the end of the course, students will be equipped with the knowledge and confidence to engage with and apply deep learning techniques in various fields, regardless of their technical background.

Objectives

Utilise the Tensorflow Keras framework to execute standard deep learning workflows.
Explore diverse data, training parameters, network architectures, and other methodologies to enhance performance and functionality.
Transition your trained neural networks into deployment to tackle practical challenges effectively.

Course Delivery

The course will be delivered in-person. There will be a significant practical element to the course and we will be working online in Google Colab notebooks.

Course Requirements

Laptop capable of connecting to the internet with a modern browser.
Familiarity with python programming basics.

Please cancel if you cannot attend

We are delighted to be able to make free at point of use training available to the research community, to enable better software and more open, reproducible research. However, free at point of use training is not free. The cost of a course can easily run to thousands of pounds, if preparation costs are taken into account.

If you sign up for a course, please make sure you either attend or cancel your booking. Bookings can usually be cancelled through myDevelopment or, failing that, by emailing n.g.gyenge@sheffield.ac.uk.

Running courses that are not fully attended wastes our funding (which is provided by taxpayers, charities and students, amongst others) and reduces our collective capacity to improve research outputs and researcher experiences.

Persistent failure to attend booked courses might result in you being excluded from future training opportunities.