| Unit name | Artificial Intelligence in Engineering Project |
|---|---|
| Unit code | CADEM0031 |
| Credit points | 60 |
| Level of study | M/7 |
| Teaching block(s) |
Academic Year (weeks 1 - 52) |
| Unit director | Dr. Iryna Tretiak |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Civil, Aerospace and Design Engineering |
| Faculty | Faculty of Science and Engineering |
Why is this unit important?
The Engineering with Artificial Intelligence Group Project provides students with first-hand experience of working in an interdisciplinary engineering team, and enables students to exercise and consolidate their design, engineering, AI implementation, and management skills in the context of a complete AI-integrated engineering system design study. A task brief is provided inspired by a real and current industrial challenge requiring AI-driven solutions and provides a challenging multidisciplinary development task that bridges traditional engineering with modern AI capabilities. Throughout the project, the students will perform concept selection and AI model architecture decisions before a preliminary project review, followed by implementation, model training, and validation that will lead to a group presentation. Teamwork is an important skill due to the multi-disciplinary nature of AI-driven engineering design, requiring collaboration between domain experts, data scientists, and systems engineers. This unit enables students to put their engineering knowledge and AI skills into practice, preparing them for their future careers in an increasingly AI-driven industry.
How does this unit fit into your programme of study?
The Engineering with Artificial Intelligence Group Project is a core pillar for the MSc programme. The unit enables students to apply their background knowledge and skills, as well as those developed through the taught component, to solve a challenging engineering task that requires the integration of AI technologies with engineering solutions in a multi-disciplinary team.
An overview of content
You will work in a multidisciplinary engineering team tasked with tackling a real-world engineering challenge through applying AI technologies. Throughout this journey your team will work collaboratively to design, develop, evaluate and demonstrate the application of AI solutions in Engineering. The project task will be set to reflect a current engineering challenge, with industrial guidance and support. Your team will work collaboratively to understand and homogenise datasets, build data-pipelines, evaluate modelling strategies, apply AI technologies to tackling the industrial challenges, and demonstrate the feasibility of your proposed solutions to a technical audience. At the end of the project, your team is expected to propose a clear AI-driven technical solution to the project challenge.
How will students, personally, be different as a result of the unit
Upon completing the group project, you will have gained practical experience in working in a multi-disciplinary team and would develop a deep understanding of the different stages of an engineering project, from conceptual design to project delivery. You will develop skills in project planning, management and will get the chance to develop your technical communication skills working within a multidisciplinary engineering team. Additionally, you will gain a deeper understanding of the different AI technologies used in engineering applications through putting these technologies to use solving a practical engineering problem, which requires critically evaluating and ranking the different approach and making decisions on development directions. You will learn first hand about the complexities involved in integrating AI in Engineering application and how to tackle them.
Learning Outcomes:
Students will undertake the project in teams. Advisors will be assigned to each group to provide technical support through regular meetings. Review meetings will be held with project partners at key stages during the project. Technical seminars and workshops will be offered for selected topics and analysis tools. Students are expected to learn through self-directed research and collaborative work, to complement their technical knowledge from units and seminars taught in the programme.
Tasks which help you learn and prepare you for summative tasks (formative):
All teams will receive regular formative feedback through supervised team meetings, with regular planned reviews with industrial partners.
4 weeks into the project, each group is required to deliver a formative short presentation to a review panel, formed of the MSc programme team, unit director and project supervisor, in order to receive feedback on their current progress, plans and their presentation delivery. This will link to both the summative group written report and summative group presentation.
Tasks which count towards your unit mark (summative):
Where a disability prevents a student from undertaking a specific method of assessment, the school will make reasonable adjustments to support a student to demonstrate the ILO by an alternative method or with additional resources.
When assessment does not go to plan
If reassessment is required, you will prepare an individual written report worth 100%. For the individual reassessment, you may be asked to develop a selected parts of your group submission and produce a critique of the other parts (including highlighting improvements that could be made to the group report) and/or you may be given a different task or goal associated with the original engineering task. The precise form of the reassessment will depend on which learning outcomes were not successfully demonstrated in your original assessments.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. CADEM0031).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
