8233 modules
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MANG3096 2029-30
Advanced Digital Marketing
This module aims to develop an understanding of the major issues facing marketers in the rapidly growing area of online marketing, with an emphasis on the managerial implications of evolving business models and the associated new marketing applications. Students will acquire specialist knowledge in a rapidly developing subject area where employers are reporting significant skills shortages. This includes data-driven marketing and the understanding of the tools and applications that can be applied to different types of marketing challenges. Students on this module will be given real-life unstructured marketing problems to work on and solve. They will be required to draw on leading-edge academic research and industry-based thought leadership to approach challenges in creative ways. -
MANG3096 2028-29
Advanced Digital Marketing
This module aims to develop an understanding of the major issues facing marketers in the rapidly growing area of online marketing, with an emphasis on the managerial implications of evolving business models and the associated new marketing applications. Students will acquire specialist knowledge in a rapidly developing subject area where employers are reporting significant skills shortages. This includes data-driven marketing and the understanding of the tools and applications that can be applied to different types of marketing challenges. Students on this module will be given real-life unstructured marketing problems to work on and solve. They will be required to draw on leading-edge academic research and industry-based thought leadership to approach challenges in creative ways. -
MANG3096 2027-28
Advanced Digital Marketing
This module aims to develop an understanding of the major issues facing marketers in the rapidly growing area of online marketing, with an emphasis on the managerial implications of evolving business models and the associated new marketing applications. Students will acquire specialist knowledge in a rapidly developing subject area where employers are reporting significant skills shortages. This includes data-driven marketing and the understanding of the tools and applications that can be applied to different types of marketing challenges. Students on this module will be given real-life unstructured marketing problems to work on and solve. They will be required to draw on leading-edge academic research and industry-based thought leadership to approach challenges in creative ways. -
ARTD6308 2026-27
Advanced E-textiles in Wearable Technologies
This module will advance your ideation, research, design and practical skills in the development and application of E-textiles for wearable technologies and other market sectors. You will increase your understanding of key materials, technologies and processes, alongside good design principles, innovation and identification of market specialisms and future trends. -
ECON3040 2028-29
Advanced Econometrics with Machine Learning
Building on the econometric content learned in the second year this module introduces students to advanced econometric methods and machine learning. The module will first introduce an empirical problem then it will introduce the classical econometric answer to that problem and discuss how that method can fail. Then we will introduce machine learning methods that address potential failures of the classical econometric method, learn how to implement them in statistical software to then look at applications. Finally, we also discuss potential problems of the machine learning method. We will repeat this procedure with multiple topics. The goal of the course will mainly be prediction accuracy of the methods but extensions to causal inference and meaningful policy evaluation will also be mentioned. Applications to economic problem will be used throughout to illustrate the methods. -
ECON3040 2027-28
Advanced Econometrics with Machine Learning
Building on the econometric content learned in the second year this module introduces students to advanced econometric methods and machine learning. The module will first introduce an empirical problem then it will introduce the classical econometric answer to that problem and discuss how that method can fail. Then we will introduce machine learning methods that address potential failures of the classical econometric method, learn how to implement them in statistical software to then look at applications. Finally, we also discuss potential problems of the machine learning method. We will repeat this procedure with multiple topics. The goal of the course will mainly be prediction accuracy of the methods but extensions to causal inference and meaningful policy evaluation will also be mentioned. Applications to economic problem will be used throughout to illustrate the methods. -
SESM6034 2026-27
Advanced Electrical Systems
To provide an introduction to power system analysis and power electronics, and an in-depth coverage of electrical machine operation and design in the context of applications from the fields of renewable energy, marine propulsion, robotics and electric vehicles. -
SESM6034 2028-29
Advanced Electrical Systems
To provide an introduction to power system analysis and power electronics, and an in-depth coverage of electrical machine operation and design in the context of applications from the fields of renewable energy, marine propulsion, robotics and electric vehicles. -
SESM6034 2025-26
Advanced Electrical Systems
To provide an introduction to power system analysis and power electronics, and an in-depth coverage of electrical machine operation and design in the context of applications from the fields of renewable energy, marine propulsion, robotics and electric vehicles. -
SESM6034 2029-30
Advanced Electrical Systems
To provide an introduction to power system analysis and power electronics, and an in-depth coverage of electrical machine operation and design in the context of applications from the fields of renewable energy, marine propulsion, robotics and electric vehicles.