Module ENGI1151: Computational Tools for Engineers and Scientists

Department: Engineering

ENGI1151: Computational Tools for Engineers and Scientists

Prerequisites

• A-level Mathematics at Grade A

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• To equip students with fundamental techniques in the use of computational tools in Engineering.
• To give an awareness of the importance of computational tools in the modern world and the impact it has on technological advances and in research practise both within and outside Engineering.
• To introduce students to the application of computational tools in a range of settings across Engineering.

Content

• Introduction to a high-level programming language for Engineering application. This is a language primarily intended for numerical computations. Typically Python will be used, though other languages may be selected by the course leader in particular applications.
• Using library functions or toolboxes, how to build on the work of others.
• Data manipulation, analysis and visualisation using high-level programming languages.
• Using computational tools for Engineering analysis. This will typically cover optimisation, stochastic analysis and machine learning problems.

Learning Outcomes

• An understanding of how a Engineering analyses are carried out.
• An appreciation of the role of Engineering and computational tools in the modern world.
• An understanding of several approaches to analysing Engineering data.
• An appreciation of the practical limitations of computational tools in Engineering.
• AHEP4 Learning Outcomes: In order to satisfy Professional Engineering Institution (PEI) accreditation requirements the following Accreditation of Higher Education Programmes (AHEP4) Learning Outcomes are assessed within this module:
• C2. Analyse complex problems to reach substantiated conclusions using first principles of mathematics, statistics, natural science and engineering principles.

• On completion of the module, students will be able to write software programs to analyse Engineering data.
• On completion of the module, students will be able to use off-the-shelf packages and libraries to analyse Engineering data.
• On completion of the module, students will be able to select the appropriate computational tool for the problem at hand and be able to discuss the merits of their chosen approach
• On completion of the module, students will be able apply off-the-shelf or bespoke programs to carry out Engineering analysis.

• Structured presentation of information in written form.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Lectures enable the students to learn new material and provide structure and guidance to the student’s own activity.
• Online practical classes enable the students to put into practice learning from lectures and strengthen their understanding through application.
• Students are assessed using coursework as this allows suitably complex problems to be presented to them.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Examples and exercises are given throughout the course, to be undertaken and then discussed in practical sessions. Formative Laboratory Report.

■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.