Last modified: 27 Feb 2018 18:42
Artificial intelligence has helped solve complex practical problems such as driving a car, translating text from/to different languages, understanding and answering questions, and playing games such as chess and Go. This course will provide students of our MSc in AI with skills to help them engineer AI systems, equiping them with solid programming skills, and using state-of-the-practice languages, tools and technologies.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Session | First Sub Session | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Old Aberdeen | Sustained Study | No |
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The course will equip students with knowledge and practical skills for AI system building. The first part of the course will cover core AI topics and how to build small-scale working prototypes for these (e.g., search, reasoning, natural language processing, game playing, machine learning, planning, and others), with an emphasis on efficiency and use of state-of-the-practice technologies. The second part of the course will present methods, tools and technologies for building practical and large-scale AI systems. Topics will include integrating and extending libraries, programming for distributed environments (e.g., distributed files systems for big data), software engineering for AI systems (including knowledge engineering, project management, and others).
Information on contact teaching time is available from the course guide.
In-course assessment (50%); Written Exam (50%).
Resit: where a student fails the course overall they will be afforded the opportunity to resit those parts of the course that they failed. 1 two-hour written examination (50%) and continuous assessment mark (50%) where the mark for the passed part is 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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