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Module Specifications.

Current Academic Year 2024 - 2025

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Date posted: September 2024

Module Title Practicum (Artificial Intelligence)
Module Code CA689 (ITS) / CSC1149 (Banner)
Faculty Engineering & Computing School Computing
Module Co-ordinatorMohammed Amine Togou
Module TeachersAndrew Mccarren, Brian Davis
NFQ level 9 Credit Rating 30
Pre-requisite Not Available
Co-requisite Not Available
Compatibles Not Available
Incompatibles Not Available
None
Description

In the final semester, from May to August, students work on a practicum or major Artificial Intelligence research project of a practical and applied nature . Here, the students individually or in small teams develop prototype systems to solve a real-world problem. The projects, which may be sponsored by external clients or involve some of the students' or staff's own ideas, typically require feasibility studies followed by the creation of a project plan, and the development of a rigorously validated research experiment in Artificial Intelligence. The final research output involves the production of a scientific report/paper. This also allows students to work on projects for external or funding organisations.

Learning Outcomes

1. Formulate a research problem for a given topic Artificial Intelligence.
2. Demonstrate improved research project management and research integrity skills.
3. Apply research skills and methods to a research problem in Artificial Intelligence.
4. Demonstrate a critical understanding of the state of the art for a select research problem in AI.
5. Implement a solution to a select research problem in AI as a measurable software demonstrator.
6. Evaluate a solution to select research problem in AI using appropriate metrics.
7. Demonstrate a command of scientific writing skills via the production of a practicum report/research paper.
8. Demonstrate research communication and dissemination skills via a practicum presentation(viva).



Workload Full-time hours per semester
Type Hours Description
Independent Study750Research Skills Development, Research Proposal development, Literature Review, Scientific Writing, Data Analysis, Dataset Engineering, Scientific Programming, Research Ethics, Data Protection
Total Workload: 750

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

Practicum (Artificial Intelligence)
Students will undertake their practicum under the supervision of a staff member or affiliated industrial partner. The practicum will be delivered in the form of a scientific report/paper end of August/September A defense of their work will take place after delivery of report/paper

Assessment Breakdown
Continuous Assessment100% Examination Weight0%
Course Work Breakdown
TypeDescription% of totalAssessment Date
Research PaperStudents will undertake their practicum under the supervision of a staff member or affiliated industrial partner. The practicum will be delivered in the form of a scientific report/paper end of August/September A defense of their work will take place after delivery of report/paper100%Other
Reassessment Requirement Type
Resit arrangements are explained by the following categories:
Resit category 1: A resit is available for both* components of the module.
Resit category 2: No resit is available for a 100% continuous assessment module.
Resit category 3: No resit is available for the continuous assessment component where there is a continuous assessment and examination element.
* ‘Both’ is used in the context of the module having a Continuous Assessment/Examination split; where the module is 100% continuous assessment, there will also be a resit of the assessment
This module is category 2
Indicative Reading List

    Other Resources

    None

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