DCU Home | Our Courses | Loop | Registry | Library | Search DCU

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Application Domains 3
Module Code CA4025
School School of Computing
Module Co-ordinatorSemester 1: Andrew Way
Semester 2: Andrew Way
Autumn: Andrew Way
Module TeachersAndrew Way
Cathal Gurrin
NFQ level 8 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
Coursework Only
Reassessment of this module will consist of reassessed coursework element(s).

This module presents students with a series of domains in which data analytics have had, or are having, a transformative effect on our lives. Students will emerge with a familiarity and an understanding of how data analytics, visualisation and other aspects of data science are being used to change the world in which we live. Application domains will be chosen based on currently relevant or topical themes and availability of expert guest lectures. Potential options identified for this module are ethical AI, responsible AI, and green AI.

Learning Outcomes

1. Explain applications of data science and data analytics in 3 different domains (e.g. ethical AI, green AI, responsible AI)
2. Summarise the main issues and challenges for data-driven approaches in the 3 domains
3. Debate the scope of data-driven approaches to major aspects of our lives in the 3 domains
4. Predict potential for other data-driven approaches to major aspects of our lives in other domains

Workload Full-time hours per semester
Type Hours Description
Online activity36A series of guest lectures from industry and enterprise partners in each of the 3 application domains for this module
Assignment Completion36Completion of assignments
Independent Study115No 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 Assessment100% Examination Weight0%
Course Work Breakdown
TypeDescription% of totalAssessment Date
AssignmentExamine codes of conduct for software engineering and adapt to data science/AI practitioners20%Week 23
Extended Essay / DissertationExamine how AI systems should be assessed to ensure they are being used for good50%Week 26
AssignmentGather data related to nutrition, physical activity & sleep, and perform data analysis to predict wellbeing30%Week 30
Reassessment Requirement Type
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
This module is category 1
Indicative Reading List

    Other Resources

    Programme or List of Programmes
    DSBSc in Data Science

    My DCU | Loop | Disclaimer | Privacy Statement