COMP50070 ML CRT Placement

Academic Year 2023/2024

The aim of this module is to provide students with practical exposure to working in industry during which they can use and enhance technical skills that they have already gained through their other activities. The student will work in a setting that reflects their interests as a machine learning professional. Internships may vary considerably but in general terms the students will be placed in industrial, government, international research, or other environment where they will obtain a breadth of practical experience to complement their degree programme. The students will experience workplace culture making them more effective employees following graduation.

The exact nature of the work that students will undertake will vary according to the nature of the organizations that they join, however, the student will be expected to take a full part in the activities of the organization that they join and to make positive contributions to that organization. In contrast with routine work, a placement is defined as a learning experience incorporating mentoring, and professional supervision in which work is viewed from critical and evaluative perspectives. To facilitate this, students will be required to maintain a weekly log book and reflective diary which will describe the student’s activities and what they have learned from these. Following the placement the students will prepare a report on their activities.

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Curricular information is subject to change

Learning Outcomes:

At the end of this module, the student will be able to:

1. Work in a professional environment.
2. Apply their academic experience and their theoretical knowledge in a professional setting.
3. Demonstrate an ability to self-organize, to prioritize tasks and to work effectively to deadlines, serving the needs of key stakeholders within a professional context.
4. Reflect on the learning experience and outcomes of their internship.
5. Produce a professional report describing the details and experiences of their internship and the details of the particular project on which they worked.
6. Summarise the outcomes of their internship.

Indicative Module Content:

Not applicable for placement module.

Student Effort Hours: 
Student Effort Type Hours
Autonomous Student Learning

40
Placement/Work Experience

400
Total

440
Approaches to Teaching and Learning:
This module will be primarily based on experiential learning. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Lab Report: Reflective report on the experience of the placement. Varies over the Trimester n/a Pass/Fail Grade Scale Yes

100

Carry forward of passed components
No
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Self-assessment activities

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 

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