| Unit name | Foundations of Practice-Oriented AI |
|---|---|
| Unit code | COMSM0152 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 4 (weeks 1-24) |
| Unit director | Dr. Cussens |
| 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 Computer Science |
| Faculty | Faculty of Engineering |
Why is this unit important?
This unit covers the main topics in data-driven AI, knowledge-intensive AI and human-AI interaction. It situates those topics within human-centred and participatory methodologies to bring those AI techniques into practice. Students also study the legal and ethical context ensuring that they know how to deploy AI solutions responsibly and in a manner beneficial to society. As such it forms the foundation of the students’ AI research and practice throughout the programme.
How does this unit fit into your programme of study?
The unit runs for 8 weeks in TB1 and 8 weeks in TB2, ending before students start work on their Summer Project. The PrO-AI PhD programme has a focus on project work: both group projects and individual ones. This unit provides that training which cannot be provided by project work – key AI methods that are not specific to a particular project, as well as the general legal and ethical context within which AI is conducted.
An overview of content
Content will include, but is not limited to, the following topics and discussion questions:
How will students, personally, be different as a result of the unit?
The unit will expose students to a very wide range of AI methods and the social, ethical and legal questions they give rise to. Throughout there is a focus on how AI techniques can be used to solve particular problems in a particular domain working with particular domain experts. As a result the unit will provide a solid foundation for the students’ work on their Practice and Summer Projects and for their individual PhD study.
Learning Outcomes
Upon successful completion of this unit students will be able to:
There are two sessions each week: one to present the state of the art in a particular topic, the second for a group discussion guided by prior reading and discussion questions. The sessions are student-led using ‘flipped classroom’ techniques.
Tasks which help you learn and prepare you for summative tasks (formative):
There are no formal formative assessment points. However, the students’ Academic Mentors attend the teaching sessions with the aim of gauging their mentee’s knowledge and identify areas where further study is beneficial.
Tasks which count towards your unit mark (summative):
At the end of each Teaching Block students submit an essay of about 5,000 words (10 pages) on a research topic jointly chosen by them and their Academic Mentor. The essay should describe the background, state of the art, and open challenges with regard to the chosen topic. Each essay is assessed on a pass/fail basis in terms of scholarly content and academic writing. Narrative feedback is also provided, indicating strong points as well as areas for improvement. Passing the unit requires passing both essays.
When assessment does not go to plan
If a student’s essays do not meet the pass mark they will be required to resubmit their essay(s).
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. COMSM0152).
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.
