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Module Specifications

Archived Version 2022 - 2023

Module Title
Module Code

Online Module Resources

NFQ level 9 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None

This module provides students with a grounding in some of the most important topics in real world applications of Artificial Intelligence. Topics to be covered include human cognition, sensing people and sensing their contexts, computer vision and machine learning, search and information retrieval, semantic web and linked data. The techniques covered in the machine learning component have applicability right across the AI landscape including Fintech, education, language processing, and more.

Learning Outcomes

1. Understand the structure of the brain and how human cognition, human memory, and human thought processes work based as targets for what Artificial Intelligence applications should strive for an aim at
2. Understand how we can use AI techniques to sense and understand human activities, biometrics and behaviour and in particular how machine learning can be used. Uses of machine learning in this context is also applicable to other AI application areas
3. Information seeking and searching and information finding are the most common tasks we do in our day-to-day lives. This module equips the student with knowledge and understanding of how AI applications like information seeking, question answering, information retrieval, searching and in particular web search, operate
4. The first and possibly still most successful application of machine learning is in image and video processing. This module offers the student an understanding and appreciation of how machine learning as an application of AI, has evolved and has allowed computer vision applications like object and activity recognition, to become robust, effective and mainstream
5. An understanding of how linked data and semantic web technologies operate and are used

Workload Full-time hours per semester
Type Hours Description
Directed learning36Online learning material on FutureLearn
Independent Study151No Description
Total Workload: 187

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Assessment Breakdown
Continuous Assessment% Examination Weight%
Course Work Breakdown
TypeDescription% of totalAssessment Date
Reassessment Requirement
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
Indicative Reading List

    Other Resources

    39255, Online MOOCs, 0, Course is delivered entireley on the FutureLearn platform,
    Programme or List of Programmes