Applied Statistics|Artificial Intelligence|Buildings Conservation|Fine Art|Information and Data Science|Software Engineering|Statistics|Sustainable Heritage

Machine Learning is a powerful method of using data to make predictions. The applications to the heritage sector are innumerable, ranging from heritage...

Machine Learning for Heritage (BENV0115)

Machine Learning is a powerful method of using data to make predictions. The applications to the heritage sector are innumerable, ranging from heritage recognition and identification, to managing archives and repositories. This project-based module will offer an introduction to the different forms of machine learning strategies (Linear Regression, Logistic Regression and Neural Networks), alongside the opportunity to apply and further explore these tools through a practical project rooted in heritage practice.

DATA QUALITY|RESEARCH DESIGN|RESEARCH METHODS|RESEARCH PROPOSAL|DISSERTATION|

This module provides students with the essential skills required to commission and critique research, and become critical consumers of secondary data and...

Research Concepts and Methods (BENV0010)

This module provides students with the essential skills required to commission and critique research, and become critical consumers of secondary data and models using that data. It also prepares students to develop a clear research question and research design, select appropriate methods and samples and undertake a critical literature review – all essential skills for undertaking their dissertations.

Studying this module students will investigate the causes and effects of the recurrent and relatively strong fluctuations, (known as ‘booms’ and...

Construction Booms and Slumps (BCPM0003)

Studying this module students will investigate the causes and effects of the recurrent and relatively strong fluctuations, (known as ‘booms’ and ‘slumps’), that occur in construction and property markets. This is applicable in both volumes and prices.

It places particular emphasis upon the inter-relationships between property and construction markets, as students are introduced to the possibilities, and problems, of measuring and forecasting volume and price changes.

As part of this module, lectures may cover the following:

What are business cycles, building cycles and property cycles?
	Why does each of these cycles occur? Why do they vary in strength over periods of time and between countries?
	How do economic actions in the construction and property development processes behave to generate cycles and how do they respond to such cycles? Behavioural irrationality?
	What are our resources for measuring construction and property cycles?
	Can we forecast construction and property cycles?
 