University of Sydney

This course examines the fundamental concepts, methods and techniques of usability engineering. 

This course examines methods to model and analyze statistical dependencies in data. The methods are useful for detecting, analyzing and making inference about patterns and dependences within the data so as to support business decisions. This course offers an insight into the main statistical methodologies for modelling statistical dependence in both discrete and continuous business data. This provides the information required for a range of specific tasks, e.g. in financial asset valuation and risk measurement, market research, demand and sales forecasting and financial analysis, among others. The course emphasizes real empirical applications in business, finance, accounting and marketing, using modern software tools.

This course examines the mechanisms that drive neurons and neural circuits throughout the brain and body. The lectures explore how environmental and neuronal signals are translated into and encoded in nerve impulses and how this information is conveyed through synapses to transmit information about the external world to control the body as well as different behaviors and to store information for future use (learning and memory). The mechanisms by which sensory and motor information are integrated through neural circuits in the brain and spinal cord are also explored in detail. Practical classes provide an accessible and engaging experience to delve into the inner workings of neurons and sensory systems. 

This course examines the relationship between crime, law, medicine and science. It focuses on criminal detection practices, death investigation systems, the coroner's office, autopsies and socio-legal management of the dead body, human tissue and organ controversies, and the role of medicine, science and psychology in criminal justice.

This course examines Asia's cultures, track its political evolution from pre-colonial to post-colonial times, and explains its renewed prominence in contemporary global affairs.

This course examines the methods and techniques to efficiently explore and analyze large data collections. Students will learn how to ingest, combine and summarize data from a variety of data models which are typically encountered in data science projects, such as relational, semi-structured, time series, geospatial, image, text. As well as reinforcing their programming skills through experience with relevant Python libraries, this course will also introduce students to the concept of declarative data processing with SQL, and to analyze data in relational databases. Students will be given data sets from, eg. , social media, transport, health and social sciences, and be taught basic explorative data analysis and mining techniques in the context of small use cases. The course will further give students an understanding of the challenges involved with analyzing large data volumes, such as the idea to partition and distribute data and computation among multiple computers for processing of 'Big Data'.

This course examines target organ toxicology (lung, liver, CNS), environmental toxicology (such as asbestos and pesticides) and the diverse world of plant and animal toxins. The fundamental mechanisms for toxic reactions in the human body will be explored. As a final consequence of exposure to many toxicants, the biology and causes of cancer are discussed. As part of the course, students will be introduced to methods for the collection and analysis of data from human and animal populations, including clinical trials, forensic problems and epidemiological data. 

This course examines the complex richness of 'Americanness'. Divided into historically grounded modules (Race; Religion; Gender; Politics; Region), the course will approach each from a variety of angles: the historiographical, the literary, the cultural, the political, the cinematic. It will open lines of interrelation between historical and imaginary forms in the construction and ongoing redefinition of the United States.