The Essex website uses cookies. By continuing to browse the site you are consenting to their use. Please visit our cookie policy to find out which cookies we use and why.
View cookie policy.
Component
PhD Data Science options
Year 1, Component 06
CE802-7-AU or MA336-7-SP
CE802-7-AU
Machine Learning
(15 CREDITS)
Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.
Artificial intelligence and machine learning with applications
(15 CREDITS)
Artificial Intelligence is the science of making computers and machines to produce results and behave in a way that resembles human intelligence. This multidisciplinary activity involves the knowledge of different disciplines such as computer science, Mathematics and statistics, but also includes important elements from philosophy, logic and even psychology. Nowadays, AI is well embedded in our society from self-driving cars to spam filters, and from finance trading to video games. All predictions state that more and more of our society will depend on this technology with the consequent transformation of our society and economy. The impact of AI affects any discipline and therefore it is important for everyone to understand its principles, applications and limitations. This module is suitable for any student regardless of their background.
This module will provide you with a broad overview of AI, as well as more detailed understanding of core concepts and models. We will follow an approach both theoretical and practical, describing the theory and fundamentals of machine learning models, as well as showing how to implement them and their applications.
At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.
The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications. The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and
Ordinances and in the University Regulations, Policy and Procedures.