Module finder

This module was co-designed by LCL students and staff, and it is aimed at preparing participants for a period of cultural immersion (abroad) in their third year.

Participants will be informed about the third-year assessment, Residence Abroad Portfolio (RAP), and clarify the links between their RAP and specific teaching and learning experiences taking place in years two and four.

This module prepares you for writing the Masters dissertation. It includes both taught sessions and one-to-one tutorials.

This module prepares you for writing the Masters dissertation. It includes both taught sessions and one-to-one tutorials.

In this module students will consider ethical challenges that arise when caring for children, young people and their families / carers. They will consider children and young people across the care settings including acute care, community and hospice/respite care. Students will develop an in-depth understanding so that they can discuss and debate the ethical challenges that may arise in Children’s Nursing. They will consider communication skills and how to deliver sensitive and empathetic nursing care to children, young people and their families.

In this module students will consider ethical challenges that arise when caring for children, young people and their families / carers. They will consider children and young people across the care settings including acute care, community and hospice/respite care. Students will develop an in-depth understanding so that they can discuss and debate the ethical challenges that may arise in Children’s Nursing. They will consider communication skills and how to deliver sensitive and empathetic nursing care to children, young people and their families.

The module is designed to introduce a range of Management Science techniques, it is the level 1 module in the prescriptive analytics stream for the Business Analytics programmes.
This module will describe many of the classical MS problems and solution techniques and illustrate their use and effectiveness. You will have the opportunity to explore the process of understanding, formulating, solving and analysing a number of practical problems using the tools and techniques introduced in the module.

The module is designed to introduce a range of Management Science techniques, it is the level 1 module in the prescriptive analytics stream for the Business Analytics programmes.
This module will describe many of the classical MS problems and solution techniques and illustrate their use and effectiveness. You will have the opportunity to explore the process of understanding, formulating, solving and analysing a number of practical problems using the tools and techniques introduced in the module.

MANG2089 introduces simulation. As an experimental technique, simulation is one the most widely used modelling techniques. This is because, unlike optimising techniques such as queuing theory, it requires few assumptions. As a result, analysts use it to solve a wide variety of complex real-life problems. It is very effective. For example, a quick look at the clients of the Simul8 corporation (http://www.simul8.com/), one of the main simulation software vendors, reveals a long and impressive list of organisations who apply simulation. Students who successfully complete MANG2089 acquire the practical skills needed to conduct a successful simulation project from scratch, and have a theoretical understanding that is essential for the effective use of this powerful decision-aiding tool. Specifically, students will acquire theoretical understanding of and develop practical modelling skills in using three types of simulation:

(i)Monte Carlo simulation to model complex but static problems for which changes over time are not important such as inventory control, forecasting and decision analysis;
(ii)Discrete Event Simulationto model the operational behaviour of systems with complex queues such as hospitals, airports and supermarkets; and
(iii)System dynamics to model long-term, strategic problems such as the long term effects of government policy decisions on the health care system.

MANG2089 introduces simulation. As an experimental technique, simulation is one the most widely used modelling techniques. This is because, unlike optimising techniques such as queuing theory, it requires few assumptions. As a result, analysts use it to solve a wide variety of complex real-life problems. It is very effective. For example, a quick look at the clients of the Simul8 corporation (http://www.simul8.com/), one of the main simulation software vendors, reveals a long and impressive list of organisations who apply simulation. Students who successfully complete MANG2089 acquire the practical skills needed to conduct a successful simulation project from scratch, and have a theoretical understanding that is essential for the effective use of this powerful decision-aiding tool. Specifically, students will acquire theoretical understanding of and develop practical modelling skills in using three types of simulation:

(i)Monte Carlo simulation to model complex but static problems for which changes over time are not important such as inventory control, forecasting and decision analysis;
(ii)Discrete Event Simulationto model the operational behaviour of systems with complex queues such as hospitals, airports and supermarkets; and
(iii)System dynamics to model long-term, strategic problems such as the long term effects of government policy decisions on the health care system.

Organisations are typically faced with many decision problems in the running of their operations and they strive to make better decisions by finding good, or ideally the best (optimal), solutions to such problems. This module is concerned with how decision problems can be formulated mathematically and solved optimally to support the decision making process in organisations. The module will introduce several optimisation techniques and illustrate the application of these techniques on problems from different types of industries.

The techniques introduced in this module have a wide range of applicability on decision problems arising in, among others, resource and workforce planning, business investment, machine scheduling, logistics, and supply chain management. The underlying methods of optimisation studied in this module, however, are generally applicable and not restricted to prescriptive analytics.