Mathematical Modelling and Analysis II builds from the content and learning in ENGF0003 Mathematical Modelling and Analysis I and helps you to further develop your understanding of core mathematical concepts, and modelling and analysis skills that underpin the practice of engineering. This module will help you to develop the mathematical tools and approaches you will need throughout your career, regardless of your specialism. 
The mode of delivery for this module is a blended learning approach integrating video recorded lecture material, live weekly tutorials, structured online Moodle activities and resources, and computer programming and simulation using mathematical tools like MATLAB and spreadsheet software. Within the tutorials, you will work on set problems that reinforce taught concepts and provide an opportunity to introduce how mathematics is applied in an engineering context. As this module follows on from ENGF0003, its syllabus includes more advanced mathematical concepts in the areas of:  

Series and Transforms
	Partial Differential Equations
	Vector Calculus
	Matrices
	Statistics and Data Modelling.
Intended Learning Outcomes

At the end of this Module, providing you engage with all of the learning activities, you should be able to: 


	understand and consider the connections between mathematics and engineering, and how mathematical ideas are embedded in engineering contexts 
	
	
	analyse and evaluate real-world engineering systems in a mathematical framework 
	

	understand and apply a range of advanced mathematical concepts, including Vector Calculus, Matrices and Eigenvectors/Values, Statistics, Series and Transforms, and Partial Differential equations (PDEs) to analyse specific problems  
	
	
	identify the appropriate mathematics to study an engineering problem and find a solution 
	
	
	create appropriate computer programming, modelling techniques and statistical analysis to efficiently solve and evaluate the performance of engineering systems 
	
	
	analyse and evaluate the behaviour of the output of mathematical models to understand the underlying physical or conceptual models of interest 
	
	
	apply mathematical and engineering problem solving both collaboratively in a team and independently.
	

	generate and assess mathematical results in effective and appropriate ways to varied audiences, including non-mathematical engineering audiences.
	
 

 