| Unit name | AI in Engineering Practice |
|---|---|
| Unit code | CADEM0030 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Elsaied |
| 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?
Artificial Intelligence (AI) is rapidly reshaping the world of engineering - from predictive maintenance in manufacturing to autonomous systems in transport and intelligent design in civil infrastructure. This unit bridges the gap between theory and practice, showcasing real-world applications of AI across engineering disciplines through inspiring guest lectures from leading academics and industry experts. It’s your opportunity to explore how AI is actively solving engineering challenges today, and to reflect critically on its potential, limitations, and impact on professional practice. Whether your passion lies in aerial robotics, energy, infrastructure, or smart systems, AI in Practice will equip you with insights and tools to become an innovator in your field. This unit is essential for any aspiring engineer who wants to move beyond abstract algorithms and learn how AI technologies are deployed to solve concrete engineering problems, responsibly and effectively.
How does this unit fit into your programme of study?
This core unit supports the MSc Engineering with Artificial Intelligence by immersing you in practical, interdisciplinary case studies, and complements theoretical and technical modules such as machine learning and data science. It provides essential context, demonstrating how AI integrates with and enhances traditional engineering disciplines.
An overview of content
You will explore a range of engineering problems where AI has been successfully applied, such as aerospace, civil, mechanical and electrical engineering. Regular guest lectures - drawn from both industry and academia - will showcase diverse case studies, giving you insight into technical deployment, challenges, and decision-making. Alongside these, you will engage in discussions after lectures where you will critically analyse applications, share ideas, and explore potential future innovations.
How will students, personally, be different as a result of the unit
You will develop the ability to critically assess how AI tools are used in practice across engineering fields. You will gain confidence in discussing technical, ethical, and practical aspects of AI applications, and be able to connect theory to real-world deployment. You’ll become a more informed, agile thinker, better equipped to evaluate solutions, communicate technical insights, and develop innovative ideas in your own area of engineering.
Learning Outcomes
By the end of the unit, you will be able to:
How you will learn
This unit uses a highly interactive and applied approach, combining expert-led guest sessions with collaborative student discussion and reflective activities. Each week features a real-world case study from a different domain of engineering, showcasing diverse uses of AI. These will be followed by discussions where you explore the technical context, raise questions, and discuss implementation challenges.
You will learn through a combination of:
This active, inquiry-based learning encourages you to make meaningful connections between theoretical concepts and real-world engineering practice. The focus on communication, analysis, and reflection prepares you for careers where understanding how and why AI is applied is just as important as knowing what it is.
Tasks which help you learn and prepare you for summative tasks (formative):
You will deliver a short (5-minute) informal presentation in weeks 4–6 on a real-world AI case study of your choice. This will allow you to explore a topic in depth, receive peer and unit team feedback, and prepare for your summative tasks. A literature review plan (500 words) will be submitted in Week 6 with written feedback provided to support your final submission.
Tasks which count towards your unit mark (summative):
A critical literature review on your Research Project Topic (ILO 1,2,4)
2. Presentation (40%)
A presentation of your research Project, initial plan and discussing AI techniques that you are planning to use, including Q&A session (Week 11). This allows assessment of both research depth and communication skills. (ILO 2-4)
Both elements are must-pass. Assessments aim to support independent learning, critical thinking, and applied communication—key for professional and academic careers.
When assessment does not go to plan:
For the literature review, reassessment will involve submitting a revised version with clear response to feedback. For the presentation, an individual recorded presentation with written script and slides will be submitted, addressing the same criteria. If group collaboration was involved (e.g. peer feedback), reassessment will be individual.
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 LO by an alternative method or with additional resources.
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. CADEM0030).
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.
