Masters Compare - Find your perfect masters course.
Masters Compare - Find your perfect masters course.
Study Details: 1 year (45 weeks including summer thesis project)
Our focused master’s programme offers you a further engagement with the core skills to utilise and innovate machine learning and data approaches to creative applications. Furthermore, the ethical dimension of Artificial Intelligence (AI) is actively explored in this course ensuring you have a deep understanding of the power of this technology.
You will apply scientific principles to support creation of mathematical models of real-world problems through computer programming. Different competencies will be measured across the programme through project work, creative practice and core programming. Special attention will be given to the development of your Applied Machine Learning Final Project that targets your preferred technology sector or domain of work. This is to support your progression to industry or academic research.
You will learn using industry standard tools and advanced frameworks ensuring you are ready to progress to a wide range of roles across the technology sector.
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Sufficient prior knowledge and experience of and/or potential in a specialist subject area to be able to successfully complete the programme of study and have an academic or professional background in a relevant subject for a conversion masters.
Also, to show a willingness to work as a team player, good language skills in reading, writing and speaking, the ability to work independently and be self-motivated.
We welcome non-standard applications from diverse applicants and subject fields and applications that make a strong case for how the course could be applied to the ambitions of the applicant.
Graduates will be well placed to work in the following areas:
This unit provides an introduction to programming for digital media, focusing on its applications within creative fields. It covers key frameworks and tools that support digital media development, equipping students with practical skills for multimedia creation.
This practical class introduces students to fundamental coding concepts and develops key coding skills in the context of developing practical coding projects. Students will use coding languages such Python and JavaScript to develop chatbots and other kinds of conversational interfaces. Various approaches to chatbot design, such as flow-based, intent-based, retrieval-based, and generative-AI chatbots will be explored and developed in practical activities.
This computing and seminar unit is an introduction to data-driven insights for creative fields looking at exploratory data analysis, visualisation techniques and machine learning models for recommendation systems and personalisation.
This practical class introduces students to contemporary machine learning toolkits in order to carry out supervised and unsupervised learning approaches to media processing and generation. It also includes exploring contemporary ML approaches including CNNs, Transformers, Diffusion models, multi-modal learning and other emerging methods. Students will learn how contemporary neural networks are built and trained, as well as how custom and pre-trained models can be used and developed for interactive and human-centred applications.
This unit explores how data and machine learning can be applied to develop visual art, music and performance. Through group work, workshops, seminars and crits, students will develop hands on experience of using machine learning for live performance and the critical theory surrounding this practice.
This self-directed unit ask you to build and document a practical project and write an associated thesis report that documents your technical methods, process of design and development and evaluation.
Start your creative future at University of the Arts London About University of the Arts London (UAL) University of the Arts London (UAL) is hos...
