Last modified: 22 May 2019 17:07
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, equipping 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 |
| Co-ordinators |
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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.
Group report (50%); Class test (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 (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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