MA Public Opinion and Political Behaviour
BEng Neural Engineering with Psychology options

Final Year, Component 05

Option(s) from list
Evolutionary Computation and Genetic Programming

Evolutionary computation is an exciting area of artificial intelligence that focuses on systematic methods (known as evolutionary algorithms) inspired by Darwinian evolution for getting computers to automatically solve problems starting from a high-level statement of what needs to be done. Evolutionary algorithms are today routinely used to solve difficult problems in industry, medicine, biology, finance, and much more. Evolutionary algorithms can even consistently solve difficult problems which require solutions in the form of computer programs. This is a form of automatic programming that is known as genetic programming. In this module you will learn how to use evolutionary algorithms and genetic programming to solve real-world problems from an international authority in these areas.

Computer Vision

Computer vision is the discipline that tries to understand the content of images and videos. It has an extraordinarily wide range of applications; well-known ones include inspection on production lines, reading number plates, mixing live and computer-generated action in movies, and recognising faces. However, researchers are working on applications such as driverless cars, building 3D models from photographs, robot navigation, gaming interfaces, and automated medical diagnosis -- in fact, whenever you as a human looks at the world and try to understand what you see is fair game for computer vision. This module introduces you to the principles of computer vision through a series of lectures and demonstrations. You have an opportunity to learn how to use these principles and algorithms on real-world vision problems in the associated laboratories using the industry-standard toolkit, OpenCV.

Large Scale Software Systems and Extreme Programming

The world demands software systems with ever increasing richness of behaviours and degrees of complexity. However, traditional software engineering techniques, which were inherited with relatively minor adaptations from other, older branches of engineering, have been struggling to scale up to the challenges posed by modern software systems. As a result, a large proportion (as much as a quarter!) of software projects based on traditional methods end up being cancelled at some point in their lifecycle, with many more being late, over budget and with less features than initially stipulated. In this module you will learn why traditional software engineering techniques fail, and you will become very familiar (through lectures, labs, videos and a large group project) with a novel set of techniques, known as Extreme Programming and Agile Software Development, which fundamentally solve these problems. In the last decade, these techniques have been so successful that today as many as 80% of all projects adopt agile methods.

Body, Senses and Existence

Develop knowledge gained in the second year module, Brain and Behaviour, and deepen your understanding of how the brain affects behaviour, and the link it has with the workings of the body. You will learn from a range of experts, covering aspects from basic bodily functions to high-order existential concerns, such as psychopharmacology, diet and wellbeing, epigenetics, physical and social pain, and existential neuroscience, to ultimately gain a deep understanding of the way the brain and body interact to control behaviour.

Decision making science in theory and practice

Can psychology help make better decisions? Yes! From curbing climate change to selecting the best candidate for the job, decision-making science has many important insights to offer, which is why it is becoming increasingly popular in education, politics, business, economics and health. Governments, businesses and charities all understand the value of identifying decision pitfalls (eg social and cognitive biases) and using strategies to overcome these. In this module, you will learn about decision-making theories and gain the skills to understand, predict and improve people's decisions for real-world issues (eg "how can we help doctors better diagnose patients?", "how do we motivate people to exercise more often?", "how can we encourage people to be more prosocial?").

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