Module: Practicum (Artificial Intelligence)

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Practicum (Artificial Intelligence)
Module Code	CSC1149 (ITS: CA689)
Faculty	Computing	School	Engineering & Computing
NFQ level	9	Credit Rating	30

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 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).

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

Section Breakdown
CRN	11298	Part of Term	Semester 1, 2 & 3
Coursework	0%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	Y
Resit Category	RC2	Best Mark	N
Module Co-ordinator	Mohammed Amine Togou	Module Teacher	Andrew Mccarren, Brian Davis

Type	Description	% of total	Assessment Date
Assessment Breakdown
Research Paper	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	100%	Other

Reassessment Requirement Type
Resit arrangements are explained by the following categories; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

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

Indicative Reading List

Books:
None

Articles:
None

Other Resources

None