CS5022: Applied Artificial Intelligence

CS5022: APPLIED ARTIFICIAL INTELLIGENCE (2020-2021)

Last modified: 05 Aug 2021 13:04

Course Overview

This course will allow students to use cutting-edge AI technologies to investigate the creation and application of AI systems. Such tools include deep learning libraries and simulation environments.

Course Details

Study Type	Postgraduate	Level	5
Term	First Term	Credit Points	15 credits (7.5 ECTS credits)
Campus	Aberdeen	Sustained Study	No
Co-ordinators	Dr N. Oren

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

Any Postgraduate Programme

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?

Course Description

On this module students will apply the theoretical and practical knowledge they have gained on previous modules to undertake several AI mini-projects. Each project will exercise a different AI application library (e.g., TensorFlow, PyTorch or Keras), and students will therefore understand how AI techniques e.g., classifier and neural network systems, reinforcement learning systems and simulation/evaluation systems, can be combined to create an end-to-end deployable AI solution.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers

Details, including assessments, may be subject to change until 21st September 2026 for Term 1 and Full Year courses and 8th January 2027 for Term 2 courses.

Summative Assessments

Coursework – Computer Programming Exercise (x3)

Assessment Type	Summative	Weighting	100
Assessment Weeks		Feedback Weeks		Look up Week Numbers
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Learning Outcomes

Sorry, we don't have this information available just now. Please check the course guide on or with the Course Coordinator
Knowledge Level	Thinking Skill	Outcome

Formative Assessment

There are no assessments for this course.

Resit Assessments

Resubmission of three failed assessments.

Assessment Type	Summative	Weighting	100
Assessment Weeks		Feedback Weeks		Look up Week Numbers
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Learning Outcomes

Sorry, we don't have this information available just now. Please check the course guide on or with the Course Coordinator
Knowledge Level	Thinking Skill	Outcome

Course Learning Outcomes

Knowledge Level	Thinking Skill	Outcome
Conceptual	Understand	Students will understand how libraries for AI system creation are applied and used in practice.
Conceptual	Apply	Students will be able to combine different components into an end-to-end solution.
Conceptual	Evaluate	Students will be able to validate the effectiveness of their solution.
Conceptual	Apply	Students will be able to document – in a reproducible manner – their approach to AI system construction.
Reflection	Evaluate	Students will be able to reflect and modify their design in response to validation of an AI system’s performance.
Reflection	Analyse	Students will reflect on their new knowledge and apply it to a practical example.

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