ACS234 Mathematics and Data Modelling
Module DescriptionThis module provides an introduction to the use of analytical mathematical techniques and numerical methods and algorithms for subsequent higher level module studies and for solving a wide range of engineering problems as well. Students will develop their skills in the theory and application of core mathematics tools required for systems engineering and the application of these in system simulation and data based modelling. A brief summary of topics covered includes: complex variables and Fourier transforms, analysis of matrices and systems represented by matrices, optimisation of functions of many variables, probability, numerical integration techniques and data modelling and analysis. The module is embedded throughout with engineering examples using the mathematical techniques. Credits: 20 (Academic Year) 
Module LeaderDr HuaLiang Wei If you have any questions about the module please talk to us during the lectures or the labs in the first instance. It is likely that other students will learn from any questions you ask as well, so don’t be afraid to ask questions. Outside of lectures please contact one of us via email, or drop in to see one of us. Other teaching staffProfessor Lucy Wyatt Dr Eleanor Stillman 
Learning Outcomes 
Learning OutcomesBy the end of the module students will be able to:
This module satisfies the AHEP3 (Accreditation of Higher Education Programmes, Third Edition) Learning Outcomes that are listed in brackets after each learning outcome above. For further details on AHEP3 Learning Outcomes, see the downloads section of our accreditation webpage. 

Syllabus 
Probability Matrix Algebra – review Linear Algebra and Vector Spaces Linear Transformations Solution of Linear Equations Eigenvalues and Eigenvectors Matrix Polynomials and Exponential Optimization Least squares modelling Polynomial interpolation methods Linear regression Generalised linear regression Nonlinear regression Numerical methods for ordinary differential equations Numerical integration formulas Numerical differentiation 
Teaching Methods 
Learning and Teaching MethodsLectures: 44 hours 
Teaching Materials 
Learning and Teaching MaterialsAll teaching materials will be available via MOLE. 
Assessment 
AssessmentCoursework (20%) The resit for this module is usually by examination only. 
Feedback 
Feedback

Student Evaluation 
Student EvaluationStudents are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of the module. 
Recommended Reading 
Recommended Reading
