Learn about recent advances in the fields of data analytics, big data tools and technologies, machine intelligence while concretely experimenting on machine knowledge extraction and decision-support
Use a broad range of data science tools and technologies, from those which are established (MATLAB, R and Weka), to the new favourites which prepare you for mainstream data science jobs (Python, Jupyter notebook, Apache Spark and libraries such as Keras, TensorFlow, and PyTorch)
Graduate with important skills in strategic thinking for scientific research implementation and communication
We’ve established close relationships with companies, research and government agencies that are interested in recruiting skilled graduates in data science and artificial intelligence
Take part in organised codejams/hackathons, visit organisations and work on practical data science and artificial problems. This will support you in establishing an internship or placement
Tailor your learning towards the areas that interest you, with option units covering topics such as neuronal analysis, smart systems, computer vision and Blockchain.
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Research Methods & Professional Issues: This unit provides an overview of different research methods used to address scientific research questions. It covers aspects of research design, implementation and how they apply to solving data science and artificial intelligence based challenges in a quantitative, qualitative or mixed fashion.
Search & Optimisation: This unit introduces you to classical approaches to Search and Optimisation. These techniques are employed in a vast number of areas, including health, security, transport, aerospace, finance and many more. Whether the goal is to improve the performance of a new medicinal drug, gene states discovery and expressions, aircraft structural integrity, network traffic cybersecurity, or business investment, advanced stochastic optimisation algorithms are employed by researchers and practitioners in order to design optimal, diverse, and pertinent solutions to many real-world problems for best performing operations.
Data Processing & Analytics: The unit aims to advance your knowledge and skills in the evolving areas of big data, data modelling and analytics. You will develop a good understanding of data design, implementation and usage of data-driven systems. Moreover, you will learn how to model data and process big data, discover knowledge within the data and deal with the dimensionality of the data. Overall, you will develop critical understanding of the methodologies and techniques which lead you to process big data 5Vs, i.e. Volume, Velocity, Variety, Veracity and Value. Typical big data technology tools such as Hadoop/MapReduce, Storm, Spark, MongoDB and more are introduced.
Artificial Intelligence: The aim of this unit is to provide you with an introduction to the first principles and techniques that are employed in the greater field and sub-fields of Artificial Intelligence (AI), together with the skills and knowledge required to employ AI techniques for solving real-world and synthetic problems.
You will approach AI from a Computer Science perspective, with focuses given to the challenges faced within the field, nature inspired algorithms, and their applications to complex real-world problems.
Individual Master's Project: You will develop a good understanding of the characteristics and implications which are inherent in the solution of a complex, real-world data science and AI oriented problem. This will be achieved within the context of a substantial, independently conducted research and development work.