Neurobiology of Brain Injury and Disease II (NEUR0012)

This module will explore the neurobiological underpinnings of several neurological diseases and brain injury. It will focus on the anatomical and functional alterations in a variety of developmental, paroxysmal, neurological, and traumatic disorders. Emphasis will be put on recent research into understanding the molecular and cellular mechanisms of disease and, when applicable, how this might lead (or has led) to new therapeutic venues. Students will be encouraged to use the knowledge of functional neuroanatomy, neurophysiology and molecular and cellular neurobiology acquired as part of their Neuroscience degree course in a synoptic manner, to understand basic neuropathology.

The module will comprise a series of lectures delivered by specialists in various research areas. Students on NEUR012 will receive 1 paper to review and will be asked to deliver a written report as part of their coursework. A wrap-up session will focus on the discussion of selected aspects covered in the lectures by using a problem-based, student-led approach. Additional tutorials will provide guidelines on how to read original research articles and write review reports, and on revision and exam techniques.

Indicative lecture topics: 

PART 1: The role of the modern day neuropathologist in clinical diagnostics and research. PART 2: Neuropathology approaches in specific CNS disease
	Stroke and Brain ischaemia
	Epilepsy
	Migraines
	Down syndrome
	Spina bifida and neural tube defects
	Neuroinflammatory diseases and Multiple Sclerosis (MS)
	Myastenia gravis & Lamber-Eaton syndrome
	Prion diseases
	Traumatic Brain injury
	Brain tumors
	Problem-based wrap-up session
	Presentation of scientific papers

This module introduces students to how organisations use data and analytics to create value and improve performance, trains them to use selected statistical...

Data Analytics I (Statistics and Data Mining) (MSIN0010)

This module introduces students to how organisations use data and analytics to create value and improve performance, trains them to use selected statistical data analytics and data mining tools, and introduces them to elements of the statistical theory and algorithms that underpin those tools.

The context for the module is management in complex, innovation-intensive, data-driven environments. The explosion in the volume and range of internal and external data available to managers and the development of new data analytics tools is having a major impact on how people identify, formulate and solve management problems.

During the module, students will work with data sets from a variety of organisations and industries, and will become proficient users of R, an open-source statistical software package used by data scientists around the world.