Advanced Training in Robotics (SURG0069)

In this hands-on practical module, there will be an emphasis on technical skills and decision-making. Students will spend most of their time in the skills lab undertaking a variety of exercises and applying the theory and understanding of previous modules.

The assessments will be in-course and a final task-based assessment using a validated scoring method.

Aims of the module:

To apply the technical skills learnt in the previous modules
	To be able to undertake moderate and advanced level tasks in Robotics
	To understand the role of decision making in operating
	To learn the differences between basic and advanced Robotics
Learning outcomes:

Understanding the role of decision making in operating
	Understanding the differences between laparoscopy and robotics
	Understanding how to build an effective training programme
	Understanding the advantages of Robotics

Aims - This module aims to provide an introduction to, and practical experience of, key ideas in selected specialised topics that are at the forefront of...

Selected Topics in Statistics (STAT0017)

Aims - This module aims to introduce mathematical concepts and tools used in the finance industry, in particular stochastic models and techniques used for...

Stochastic Methods in Finance (STAT0013)

Aims - This module aims to introduce mathematical concepts and tools used in the finance industry, in particular stochastic models and techniques used for financial modelling and derivative pricing. It is primarily intended for third and fourth year undergraduate students and taught postgraduate students registered on the degree programmes offered by the Department of Statistical Science, or jointly with other departments.

Objectives - On successful completion of the module, a student should have a good understanding of how financial markets work, be able to describe basic financial products, have a good knowledge of the basic mathematical and probabilistic tools used in modern finance, including stochastic calculus, and be able to apply the relevant techniques for the pricing of derivatives.

Applications - The techniques taught in this module are widely used throughout the modern finance industry, including the areas of trading, risk management and corporate finance. They also have applications in other areas where investment decisions are made under uncertainty, for example in the energy sector where decisions on whether or not to build (i.e. invest in) new power plants are subject to uncertainty regarding future energy demand and prices.

Content - Financial markets, products and derivatives. The time value of money. Arbitrage Pricing. The binomial pricing model. Brownian motion and continuous time modelling of asset prices. Stochastic calculus. The Black-Scholes model. Risk-neutral pricing. Extensions and further applications of the Black-Scholes framework.

Key texts - Available from ReadingLists@UCL.