Last modified: 22 May 2019 17:07
This course presents the fundamental techniques of Artificial Intelligence, used in system such as Google Maps, Siri, IBM Watson, as well as industrial automation systems, and which are core to emerging products such as self-driving vehicles. This course will equip the student to understand how such AI technologies operate, their implementation details, and how to use them effectively. This course therefore provides the building blocks necessary for understanding and using AI techniques and methodologies.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Old Aberdeen | Sustained Study | No |
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This course presents a cross-section of fundamental AI techniques and technologies. Lectures will cover core concepts, theories, mechanisms and results, while practicals and tutorials will allow students to implement and use these techniques. Example topics covered in this course include approaches to searching in AI; automated planning and scheduling; AI techniques used in robotics; knowledge representation and natural language understanding.
Information on contact teaching time is available from the course guide.
Computer Programming Exercise (30%); Project Report (40%); Take Home Exam (30%).
Resit: where a student fails the course overall they will be afforded the opportunity to resit those parts of the course that they failed (pass marks will be carried forward).
There are no assessments for this course.
Formative feedback for in-course assessments will be provided in written form. Additionally, formative feedback on performance will be provided informally during practical sessions.
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