Module: Practicum (Data Analytics)

Module Specifications.

Current Academic Year 2024 - 2025

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Date posted: September 2024

Module Title	Practicum (Data Analytics)
Module Code	CA685 (ITS) / CSC1146 (Banner)
Faculty	Engineering & Computing	School	Computing
Module Co-ordinator	Mohammed Amine Togou
Module Teachers	Andrew Mccarren
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 project of a practical 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 creation of a project plan, and development of a software application or a rigorous theoretical analysis. This also allows students to work on projects for external or funding organisations

Learning Outcomes

1. extend their ability to carry out research
2. Investigate problems in a Big Data environment
3. Demonstrate improved project management skills
4. defend their work orally and through presentation, trading algorithms, fault detection, event detection and prediction, etc.;
5. proceed to further research or work within industry
6. Appreciate the context in which their practicum resides

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Independent Study	750	No Description
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

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 report in the first week of September

A defense of their work will take place after delivery of report

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Type	Description	% of total	Assessment Date
Course Work Breakdown

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