Scientific Computing 2 - 2019 entry

This module builds on your groundwork in scientific programming and introduces you to using computational methods to solve mathematical problems. You will apply your programming skills to implement various methods in numerical mathematics, including interpolation, solving linear systems and numeric integration and differentiation. You will learn how to implement numerical methods into efficient computer code, as well as how to import and make use of Python’s powerful libraries.

Contemporary mathematics and statistics are increasingly turning to the use of computationally intensive methodologies. High-level skills in programming and scientific computing are crucial for the implementation and development of modern computational tools and are necessary for the analysis and understanding of complex mathematical models and data alike.

This module will introduce you to fundamental concepts in computational mathematics using open-source software (Python). This module will run alongside other relevant first year subjects and will teach you how to use modern computing techniques to solve real-life problems.

On successful completion of this module, you should be able to:

Module Specific Skills and Knowledge:

1 Develop an understanding of a broad range of numerical methods to solve mathematical problems;

2 Develop and implement computer algorithms based on numerical procedures and pseudo code;

3 Enhance your understanding of basic programming to write more complex programs;

4 Demonstrate competency in the use of scripts and functions;

5 Develop good programming practice as is standard in science, business and industry;

Discipline Specific Skills and Knowledge:

6 Develop fundamental skills necessary to implement core and advanced techniques introduced in other modules across the programme;

7 Understand the importance of reproducibility in science and industry;

Personal and Key Transferable / Employment Skills and Knowledge:

8 Use programming to formulate and solve mathematical problems;

9 Demonstrate appropriate use of learning resources;

10 Demonstrate self-management and time management skills.

- Solving linear systems, direct and iterative methods;

- Curve fitting;

- Numerical integration;

- Numerical differentiation;

- Initial value problems.

If a module is normally assessed entirely by coursework, all referred/deferred assessments will normally be by assignment.

If a module is normally assessed by examination or examination plus coursework, referred and deferred assessment will normally be by examination. For referrals, only the examination will count, a mark of 40% being awarded if the examination is passed. For deferrals, candidates will be awarded the higher of the deferred examination mark or the deferred examination mark combined with the original coursework mark.

Basic Reading:

ELE - http://vle.exeter.ac.uk

Reading list for this module: