Through undertaking this course students will be expected to:

This is the second of four practice placement courses in the undergraduate occupational therapy programme. The course aims to broaden the students professional practice experience while assisting them to consolidate their academic knowledge and develop their clinical skills. Seven weeks of professional practice placement is embedded into the thirteen-week course. The students undertake their practice placements off campus in a variety of service settings.

This course is designed to provide applications of behavioural economics in a variety of business settings. Students are exposed to the economic paradigms, decision under risk and uncertainty, time and distributional preferences, status concerns, inter-temporal choices, human rationality, heuristics and biases, and behavioural game theory.

Big Data Analytics is regarded as one of the important emerging technologies in different fields of business including accounting, economics, finance, marketing, and management. Big data refers to data sets with large sizes that are beyond the ability of traditional data management software tools. While traditional data processing technologies are inadequate, practical knowledge addressing challenges of huge or complex data handling in terms of their analysis, transformation, visualisation and prediction is paramount in businesses. This course introduces students to various massive data sets that can be structured, semi-structured, or unstructured and sourced from multi-media, social media, cloud platforms, web, IoT and traditional economic and business databases. Students will apply data mining and natural language processing tools to these big data to gain business insights such as hidden patterns, untold facts, unknown correlations, market trends, and customer preferences. Big data from social media and financial statements now play a significant role in extracting information for making informed business decisions related to understanding customer behaviours and financial investments. Case studies on big data analytics will be utilised to design and communicate concepts and techniques used in business decision making.

Living systems are made up of molecules and this course introduces the diversity of important biological molecules and shows how their structures relate to their function. The smaller biomolecules such as amino acids, nucleotides and sugars have important biological functions of their own, and are also utilised as building blocks for biopolymers such as proteins, nucleic acids and polysaccharides. The metabolic processes that occur in cells to synthesise and degrade these biomolecules and to provide energy for the cell will be presented with a view to showing how biochemical reactions and pathways are connected and controlled.

This course provides students with an in-depth knowledge of biomass technology options for production of renewable energy (heat and electric power), fuels and chemicals that are suitable as substitutes for fossil fuels and their refined products. Students will gain insight into biomass properties and resource characteristics, utilisation concepts, treatment and conversion technologies as well as environmental consequences of bioenergy. The emphasis is on thermochemical approaches although biological methods (e.g. microbial conversion) are also covered in the course.