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CS5061: ENGINEERING AI SYSTEMS (2018-2019)

Last modified: 22 May 2019 17:07


Course Overview

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

Course Details

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
  • Dr Ernesto Compatangelo
  • Professor Ehud Reiter

What courses & programmes must have been taken before this course?

  • Either Any Postgraduate Programme (Studied) or Master of Engineering in Computing Science

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

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).

Degree Programmes for which this Course is Prescribed

  • Master Of Science In Artificial Intelligence

Contact Teaching Time

Sorry, we don't have that information available.

Teaching Breakdown

  • 10 Lectures during University weeks 10 - 11
  • 5 Practicals during University weeks 10 - 11

More Information about Week Numbers


Summative Assessments

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)..

Formative Assessment

There are no assessments for this course.

Feedback

Formative feedback for in-course assessments will be provided in written form. Additionally, formative feedback on performance will be provided informally during practical sessions.

Course Learning Outcomes

None.

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