Module Overview
Inspired by the biological neurons that make up our brains, artificial neural networks (ANNs) are simple mathematical models that date back to the work of McCulloch and Pitts in the 1940s. Today, ANNs are the powerhouses of modern AI solutions and are regarded as one of the most important technical innovations of the past decade. In this module, we will follow the chronology of the deep learning revolution, starting with the basics of deep feed-forward networks and how to train them effectively. We will then work our way forwards in time and study convolutional neural network (CNN) architectures for images, recurrent neural networks (RNN) for time series data, and unsupervised models for representation learning. Towards the end of the module, students explore how deep nets learn and study the issues that can impact their real-world utility and the implications for society at large.
Module Overview
Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection and medical imaging. Image processing is the study of algorithms that take images as an input and return information about these images. This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from raw images and interpret the result.
Module Overview
The module introduces the fundamentals of machine learning and principled application of machine learning techniques to extract information and insights from data. The module covers supervised and unsupervised learning methods. The primary aim is to provide students with knowledge and applied skills in machine learning tools and techniques which can be used to solve real-world data science problems.
Module Overview
This module aims to equip you with the skills to design and develop connected, data-driven mobile applications, leveraging smartphone sensor technologies such as location, camera and proximity sensors. Consuming RESTful web services will be an area of focus for the data driven components of mobile app development. You can utilize contemporary tools to build mobile applications by applying industry-standard techniques for both code-base development and user-centered design.
Module Overview
This module offers students the chance to demonstrate their ability to work independently on a significant, in-depth project requiring the coherent and critical application of computer science theory and skills.
Students must initially produce a project proposal and related materials to frame the work, specifying clear, specific, academically justified, and appropriately scoped aims and objectives, as well as feasible means for fulfilling those aims and objectives. Students then work independently to fulfil those project goals. Throughout this process students are expected to demonstrate the application of practical development and analytical skills, innovation and/or creativity, and the synthesis of information, ideas and practices to generate a coherent problem solution.
Module Overview
The module aims to introduce the main concepts of Autonomous Mobile Robotics, providing an understanding of the range of processing components required to build physically embodied robotic systems, from basic control architectures to spatial navigation in real-world environments.
Students will have the opportunity to be introduced to relevant theoretical concepts around robotic sensing and control in the lectures, together with a practical “hands on” approach to robot programming in the workshops.
Module Overview
This module is intended to introduce students with the fast growing area of consumer electronics design.
Apart from interface and size issues, portable consumer electronics present some of the toughest design and engineering challenges in all of technology. This module breaks the complex design process down into its component parts, detailing every crucial issue from interface design to chip packaging, focusing upon the key design parameters of convenience, utility and size.
Module Overview
Realistic physics simulation is a key component for many modern technologies including computer games, video animation, medical imaging, robotics, etc. This wide range of applications benefiting from real-time physics simulation is a result of recent advances in developing new efficient simulation techniques and the common availability of powerful hardware.
The main application area considered in this module is computer games, but the taught content has much wider relevance and can be applied to other areas of Computer Science.