Postgraduate Studentships - Search for funding opportunities.
Postgraduate Studentships - Search for funding opportunities.
Study Details: 12 months
Our MSc Data Science and AI provides the opportunity to deepen your core competencies in data science and AI, and to strengthen your skills in developing data- and AI-driven products and services. The course actively explores the ethical and social dimensions of data science and AI —ensuring you have a deep and critical understanding of the impacts of related technologies, and a familiarity with arts and human-centred methods for designing and reasoning about new systems.
Using computer programming combined with arts and humanities critical approaches, you will apply scientific and mathematical principles to guide the creation and evaluation of mathematical models of real-world problems. This enables the creation of tools that take into account the computational and technical, but also the human, social and cultural aspects that emerge from the entanglement of humans, technology and the environment. You will apply data science and AI to a broad range of domains, involving diverse types of data and content, from numerical data to text and media. And you will critically engage with contemporary thinkers from diverse disciplines concerned with the ethical and social implications of data science and AI. You will approach through collaborative, creative problem solving which leverages and strengthens your technical and teamwork skills, critical thinking, and your knowledge of application domains and stakeholders.
Your thesis project should target your preferred technology sector or domain of work, supporting your progression to industry or further academic research.
We are committed to ensuring that your skills are set within an ethical framework and are working to embed UAL’s Principles for Climate, Social and Racial Justice.
Offers will be made based on the following selection criteria:
Computing graduates are highly sought after across sectors and our degrees facilitate progression to a wide range of careers in both industry and academia. Graduates can join large companies or start their own business using their engineering skills and their knowledge of computational innovation.
Graduates can become:
You will be introduced to advanced algorithms through mathematics and programming, including linear algebra for advanced analysis of data and machine learning optimisation. You will create and analyse computational models using approaches such as stochastic and gradient algorithms, dynamic programming algorithms and primal and dual methods. This will develop your understanding of how algorithms might be improved to tackle current and emerging problems.
You will learn advanced data structures and representations, including complex multidimensional feature processing and storage. You will be asked to demonstrate your advanced knowledge and skills in a range of mathematical and statistical approaches required for carrying out modern data science and AI. This includes calculus, discrete structures, probability theory and elementary statistics. You will also approach advanced topics in statistics including complex correlations, significance, differences in nominal and ordinal data analysis, and linear algebra.
This unit will cover advanced professional practice principles, ethics, data protection legislation, compliance procedures and impact analysis. Through a series of case studies, you will be introduced to different critical approaches, such as social data science and you will explore in detail how representation and data abstraction at macro scale can impact individuals and marginalised groups. You will also learn how to story tell through various data visualization techniques and get introduced to big data tools and techniques.
This unit focuses on a range of contemporary AI and machine learning techniques and approaches such as RNN and LSTMs, GANs and VAEs. You will also cover reinforcement learning for natural language processing, personalisation, recommendation and audience analysis. As part of this unit, you will learn how to prepare datasets and create, test and validate your own models to solve real-world problems.
In this hands-on unit, you will learn how to solve problems in a critical and creative way. You will learn human-centred approaches and methods (co-design, user-centred design) for thinking and building new technologies. You will also learn to use creative tools (Bela, p5js, Pure Data, Processing) and methods (empathic design, material-oriented practices, soma design) to design and build custom digital interfaces that emerge from a problem-driven perspective.
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...
