| Unit name | Principles of Artificial Intelligence |
|---|---|
| Unit code | SEMT10005 |
| Credit points | 20 |
| Level of study | C/4 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Professor. Lawry |
| 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 Engineering Mathematics and Technology |
| Faculty | Faculty of Engineering |
Why is this unit important?
This unit introduces fundamental ideas, methods and algorithms in AI and places them in a historical context. It then links this material to key concepts from the philosophy of science concerning the nature of knowledge, data, reasoning and learning. In this way the unit will both equip students with the basics tools with which to begin to apply AI and also to put these into a broader context in which they understand the historical challenges that drove their development as well as the underlying philosophical challenges that affect all AI systems. They will gain an appreciation of how different AI paradigms have emerged, the relative strengths and weaknesses of different approaches, and how AI has both influenced and been influences by concepts in epistemology and the philosophy of mind.
How does this unit fit into your programme of study
This a core foundational unit in the BEng AI programme. It provides students with a technical background in basic AI and machine learning that will facilitate further study in state-of-the-art methods. This will include aspects of data analysis & visualization, simple supervised and unsupervised learning, logic and computation. It will also introduce the history of AI, giving a sense of how it has developed and changed, and how it has influenced the broader intellectual landscape.
An overview of content
The unit covers the core concepts and principles of AI and their historical development, as well as related philosophical ideas. The following five strands are interweaved.
How will students, personally, be different as a result of the unit
Students will gain a sense of perspective placing their current studies in AI as part of a long term endeavour to build intelligent machines. They will understand how key ideas have emerged and how those have been implemented, driven by different approaches and paradigms. They will become familiar with key concepts from philosophy of science and philosophy of mind that both inform and are informed by AI and which can provide them with tools to help contextualize the challenges and risks of modern AI.
Learning outcomes
On successful completion of this unit, students will be able to:
Students will learn through a range of activities including lectures, lectorials, workshops, problem classes and computer laboratories. Workshops will facilitate discussion of challenging ideas and concepts. Problem classes and computer laboratories will be staffed by teaching assistants and provide direct feedback on linked exercises.
Tasks which help you learn and prepare you for summative tasks (formative):
Regular problem classes and computer laboratory in which students will tackle structured exercises with feedback provided by teaching assistants and academics. Workshop discussions on concepts linking AI and the philosophy of science and mind.
Tasks which count towards your unit mark (summative):
The unit will be assessed by an in-person exam (100%) covering all Learning Outcomes.
When assessment does not go to plan:
Re-assessment takes the same form as the original summative assessment.
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. SEMT10005).
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.
