Real estate|Applied urban economics|Regional economics

This module covers the theoretical principles of economics in the context of real estate. It begins with explaining the basic concepts of economics such as...

Real Estate and Urban Economics (BCPM0095)

This module covers the theoretical principles of economics in the context of real estate. It begins with explaining the basic concepts of economics such as supply and demand, elasticity, substitution and utility. It also covers productivity of firms, people and locations and considers optimisation problems of firms and households.

The second part of the module applies these concepts to real estate. It begins with principles of urban economics including agglomeration, density and returns to scale in cities. It then examines location choices of firms and households. Finally, it reviews theories and empirical evidence of real estate cycles.

Business analytics|data science|machine learning|network analytics

The rise of digital engineering in the built environment provides not only a source of big data but also computational methodologies to harvest and analyse it....

Big Data and Business Analytics (BCPM0090)

The rise of digital engineering in the built environment provides not only a source of big data but also computational methodologies to harvest and analyse it. In this module you will be introduced to the fundamentals of business data analytics for decision-making. Organisational strategy in the area of digital engineering is closely linked to business analytics, as the industry becomes data-intensive. This module aims to provide you with a deep understanding of quantitative techniques for harvesting, cleaning, classifying, clustering, modelling and presenting data to support strategic and data-driven decision-making. The module will equip you with the intellectual and practical analytical skills to analyse business process and inform strategic decision-making.

At the end of this module you will be able to:

Understand concepts, ideas, constructs of data, databases and data analytics
	Understand principles of machine learning
	Understand concepts and implementation of networks analytics
	Identify and evaluate applications for data analytics in logistics and strategy
	Critically utilise data analytics to investigate management concepts
	Develop critical analytic thinking for strategic decision-making