Module ENGI49315: Engineering Data and Modelling

Department: Engineering

ENGI49315: Engineering Data and Modelling

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• This module is designed solely for students studying Department of Engineering degree programmes.
• To gain proficiency in data and information collection, management, modelling, analysis, interpretation and presentation techniques in the context of engineering management.
• To apply engineering system models and methods appropriate to solve engineering management problems.
• To understand the role of data management within the context of responsible decision making.

Content

• Engineering data and information: Types and sources of engineering data; information requirements; the role and importance of data-driven decision-making in engineering management.
• Data-driven modelling and interpreting: Data-driven engineering models, including simulations, data analytics, and machine learning, applied to different problems.
• Handling and controlling data: Techniques for collecting, organising, and managing engineering data effectively; data storage and documentation for engineering management.

Learning Outcomes

• An understanding of the role of engineering data and modelling within the context of engineering management.
• Knowledge of the types and sources of engineering data that enable data-driven, ethical decision-making.
• Knowledge of data-driven modelling frameworks, techniques and types.
• A knowledge and critical understanding of engineering data management, storage and documentation frameworks, standards and responsibilities.
• An appreciation of the limitations of modelling and data in responsible decision-making.

• An ability to apply comprehensive knowledge of mathematics, statistics and engineering principles from the wider engineering context to the solution of complex problems and decisions.
• An ability to formulate and analyse complex engineering problems to reach substantiated conclusions based on evidence from modelling and data, recognising where information is incomplete and using engineering judgment to address the limitations of techniques.
• An awareness of current industrial practice and an ability to identify, apply and evaluate appropriate computational and analytical techniques, while understanding their limitations. .
• An in-depth understanding of effective communication of engineering data and data-driven decision making.

• An advanced ability to communicate effectively about complex engineering matters and to engage stakeholders in the decision-making process.
• A capacity for independent self-learning within the bounds of professional practice.
• An ability to select and apply modelling and analytical skills appropriate to an engineer.

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

• The module content is delivered through mixed-mode lectures and workshops that combine taught material with live examples for students to undertaken in class, equipping students with the required problem-solving capability.
• Students can access staff Office Hours' to discuss any aspect of the module with teaching staff on a one-to-one or group basis. These are weekly sign-up sessions available to all students.
• Coursework is an appropriate mode of assessment for this module because it enables students to engage with realistic engineering problems and demonstrate their ability to determine modelling requirements, select appropriate techniques, and apply effective modelling and analysis to reach well evidenced decisions.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Formative assessment is provided by means of formative problem sheets.

■ 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.