| Unit name | Artificial Intelligence & Cognition |
|---|---|
| Unit code | SEMT30010 |
| Credit points | 20 |
| Level of study | H/6 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Dr. Houghton |
| 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?
Many of the major advances in AI were inspired by discoveries in Neuroscience and Psychology. Now the direction of influence between these fields has begun to shift. In the rapidly changing field of Cognitive AI, scientists and engineers bring together the latest advances in AI with principles from Neuroscience and Psychology to attempt to understand how the human brain produces its cognition. This remains one of the great challenges of 21st century science. This unit aims to equip you with the knowledge and skills to participate in this endeavour. You will gain not just understanding, but also the ability to apply cutting-edge AI techniques to explore and replicate complex cognitive processes, and perhaps even lead the next wave of innovations in the new field of Cognitive Artificial Intelligence.
How does this unit fit into your programme of study
This unit complements the content in other machine learning (ML) and AI units in your programme but does not depend on them. You will build on foundational knowledge of single neurons and small circuits and move towards the exhilarating world of distributed neural networks and higher cognition. You will learn important context for how current AI models are inspired by and relate to the real brain anatomy and physiology. You will also learn the strengths and limitations of such models to understand the brain.
An overview of content
During this unit, we will delve into:
How will students, personally, be different as a result of the unit
You will gain a better understanding of how your brain produces your perceptions and enables your cognitive ability. You will learn how artificial neural networks resemble and differ from brains. You will develop the ability to build and adapt cutting-edge AI techniques to explore and replicate complex cognitive processes. These skills can be a springboard for research in academia or industry.
Learning outcomes
On successful completion of this unit, students will be able to:
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including on-campus lectures/Q&A sessions, pre-recorded video lectures, and formative self-directed exercises. The unit will be supported by regular computer labs; these will provide student-centred on-campus learning through practical problem solving and will create a supportive environment where students apply for themselves the theory and methods discussed in the unit. Students will be expected to actively participate in the lectures and labs and to engage with videos, readings, self-directed exercises, presentation, debate and problem-solving activities.
Tasks which help you learn and prepare you for summative tasks (formative):
You will receive many types of formative assessment throughout the unit, which cover a range of required effort. Our aim is to create a supportive and stimulating environment in which you are willing to test your knowledge frequently with low-stakes assessment, to identify gaps in your understanding and consolidate your knowledge.
These tasks include:
Tasks which count towards your unit mark (summative):
The unit has two summative assessments: an in-person exam (weighted 50% assessing Learning Outcomes 2,3 and 4) a coursework Individual Written Report (weighted 50% assessing Learning Outcomes 1 and 4).
When assessment does not go to plan:
Re-assessment takes the same form as the original summative assessment. If you pass one of the summative assessments, then your mark for this can be carried forward towards your final mark and you will only have to be reassessed on the assessment that you did not pass.
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. SEMT30010).
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.
