The aim of this course is to enable students: (a) to recognize the connections between mathematics and engineering and how mathematical ideas are embedded in engineering problems; (b) to represent real-world systems and design problems from engineering in a mathematical framework. The module builds on the knowledge and skills gained in Modelling and Analysis I.

Upon completion of the course, a student should be able to:

Identify and draw upon a range of advanced mathematical concepts, including Analytical and Numerical solution of (systems of) ODEs, Linear Algebra, Matrices and Eigenvectors/Values, Statistics and Partial Differential Equations (PDEs)
	Analyse specific problems and identify the appropriate mathematics to realise a solution
	Employ appropriate computer programming and modelling techniques and statistical analysis to efficiently solve and evaluate the performance of engineering systems
	Relate the behaviour of the output of mathematical models to the underlying physical or conceptual models of interest
	Carry out engineering problem solving both collaboratively in a team and independently
	Present and interpret mathematical results in effective and appropriate ways to varied audiences, including non-mathematical engineering audiences.

Real estate plays a significant role in our lives with direct implications on our health and productivity, the fabric of local communities, and the stability...

Real estate plays a significant role in our lives with direct implications on our health and productivity, the fabric of local communities, and the stability of the economy as a whole. Moreover, it is the largest alternative asset class for institutional investors and the largest market by any account in most advanced economies around the world. Furthermore, being responsible for 30-40% of global carbon emissions, the real estate sector has seen a plethora of policy - and industry initiatives related to sustainability, and as such, environmental, social and governance considerations have become deeply ingrained in the analysis of real estate markets. Therefore, real estate markets are hugely consequential in our lives; however, understanding what affects them and how analysing real estate data is as important as it is difficult. The ability to obtain and process real estate data using programming languages to perform accurate statistical analyses is a fundamental asset to any professional. With these data and programming skills you will be able to answer questions such as what is the effect of air pollution on house prices, or how much are businesses willing to pay for locating their office outside a flooding risk zone, or what were the implications of Brexit on real estate development in London, among others. In this course we will dive into the analysis of real estate data using R, an open source statistical package and programming language, and we will learn which questions we can answer employing them and, more importantly, how.