| Unit name | Introduction to Artificial Intelligence |
|---|---|
| Unit code | COMS20018 |
| Credit points | 20 |
| Level of study | I/5 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Professor. Seth Bullock |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
COMS10016 Imperative and Functional Programming and COMS10018 Object-Oriented Programming and Algorithms or equivalent COMS10015 Computer Architecture and COMS10012 Software Tools or equivalent COMS10014 Mathematics for Computer Science A and COMS10013 Mathematics for Computer Science B or equivalent |
| 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?
Artificial Intelligence (AI) enables computers to achieve tasks that would otherwise need to be carried out by people. Recent rapid progress in AI has led to a huge explosion of interest in its methods and its many applications across
industry, commerce, entertainment, finance, government, and science. The power of modern AI is rapidly reshaping modern society. Consequently, developing and deploying AI responsibly and effectively has become one of the key challenges of our age.
This unit introduces students to the foundations of AI and the range of approaches and methods within it, providing a hands-on approach in labs that engage with a variety of AI systems.
How does this unit fit into your programme of study
This is a mandatory unit that is taken during TB1 in Year 2. This allows students to develop an understanding of the foundations of the field of artificial intelligence and how its different technologies are being applied.
An overview of content
This unit will teach you what artificial intelligence (AI) is. It introduces key AI topics including its history, theoretical foundations, practical applications, and philosophy: what does it mean for an artificial agent to emulate human intelligence, and can we go beyond this? It introduces key approaches in knowledge-based and data-driven AI and explores the differences between them. It will also consider AI's place in society and engage with the debate on AI safety, ethics and “AI for Good”. The unit’s approach is hands-on, providing opportunity to engage with AI systems while covering the conceptual foundations of the field.How will students, personally, be different as a result of the unit Students will be aware of state of the art in AI and understand the benefits & limitations of different AI approaches, and how these can be applied to a variety of AI problems.
Learning Outcomes
On successful completion of this unit, students will be able to:
The unit includes lectures to introduce and explain conceptual and theoretical material alongside a series of applied labs that allow students hands-on engagement with AI methods and systems.
Tasks which help you learn and prepare you for summative tasks (formative):
Teaching will take place over Weeks 1-11, with consolidation and revision sessions in Weeks 12.
The unit comprises a series of lectures covering the conceptual and theoretical foundations of AI alongside a series of practical labs engaging with a range of AI technologies. These practical labs have been designed to explore the
theoretical content of the unit in a way that prepares students for the exam and lab assessments. Labs include opportunities for students to discuss and check their progress on the learning outcomes of the unit.
Tasks which count towards your unit mark (summative)
Students will be assessed via three elements:
- A mid-term video presentation or equivalent that will assess Learning Outcome 1 (worth 20% of the unit)
- A series of laboratory-based assessments that will assess Learning Outcome 2 (worth 20% of the unit)
- An end-of-term exam that will assess Learning Outcomes 3 and 4 (worth 60% of the unit)
When assessment does not go to plan
Students will retake relevant assessments in a like-for-like fashion.
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. COMS20018).
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.
