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QC5004: APPLIED ARTIFICIAL INTELLIGENCE (2026-2027)

Last modified: 05 Dec 2025 16:46


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 Offshore Sustained Study No
Co-ordinators
  • Dr N. Oren

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

  • Any Postgraduate Programme (Studied)

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 Applied AI course will give a firm grasp of AI, its applications, its challenges related to commercial, social, and regulatory aspects with real-world use cases. On completion of this course, students will be able to apply the theoretical and practical knowledge they have gained on previous modules to undertake several AI mini-projects. Each project will exercise AI application libraries (e.g., TensorFlow 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. They will also be aware of the additional challenges an AI developer has to keep in mind, especially regarding the performance, decision accuracy, ethical, regulatory and social aspects.


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 31 August 2025 for 1st Term courses and 19 December 2025 for 2nd Term courses.

Summative Assessments

Report: Individual (includes Programming Exercise)

Assessment Type Summative Weighting 50
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualApplyStudents will be able to combine different components into an end-to-end solution.
ConceptualApplyStudents will be able to document – in a reproducible manner – their approach to AI system construction.
ConceptualEvaluateStudents will be able to validate the effectiveness of their solution.
ConceptualUnderstandStudents will understand how libraries for AI system creation are applied and used in practice.
ReflectionAnalyseStudents will reflect on their new knowledge and apply it to a practical example.
ReflectionEvaluateStudents will be able to reflect and modify their design in response to validation of an AI system’s performance.

Report: Group (includes Programming Exercise)

Assessment Type Summative Weighting 50
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualApplyStudents will be able to document – in a reproducible manner – their approach to AI system construction.
ConceptualApplyStudents will be able to combine different components into an end-to-end solution.
ConceptualEvaluateStudents will be able to validate the effectiveness of their solution.
ConceptualUnderstandStudents will understand how libraries for AI system creation are applied and used in practice.
ReflectionAnalyseStudents will reflect on their new knowledge and apply it to a practical example.
ReflectionEvaluateStudents will be able to reflect and modify their design in response to validation of an AI system’s performance.

Formative Assessment

There are no assessments for this course.

Resit Assessments

Resubmission of failed elements (pass marks carried forward)

Assessment Type Summative Weighting
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualUnderstandStudents will understand how libraries for AI system creation are applied and used in practice.
ConceptualApplyStudents will be able to combine different components into an end-to-end solution.
ConceptualEvaluateStudents will be able to validate the effectiveness of their solution.
ConceptualApplyStudents will be able to document – in a reproducible manner – their approach to AI system construction.
ReflectionEvaluateStudents will be able to reflect and modify their design in response to validation of an AI system’s performance.
ReflectionAnalyseStudents will reflect on their new knowledge and apply it to a practical example.

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