CS3701 Data Science Industry Placement 1

Academic year

2024 to 2025 Semester 2

Key module information

SCOTCAT credits

60

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 9

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Available only to students on BSc Data Science Graduate Apprenticeship.

Planned timetable

Not applicable

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr R Hoffmann

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr. Ruth Hoffmann (rh347)

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

This module provides the first extended period of work-based learning on the Data Science Graduate Apprenticeship programme. Apprentices spend four months on the employer's premises, and are expected to travel to clients or other employer offices as and when required. During the module, apprentices work on a range of projects, selected by the employer to give apprentices the opportunity to develop professional practice and to apply and integrate technical knowledge, skills and behaviours in an industrial working environment on their own and as part of a team. Projects are fully supervised at the employer; apprentice performance is assessed jointly by the immediate supervisor and a member of staff in the School of Computer Science.

Relationship to other modules

Pre-requisites

BEFORE TAKING THIS MODULE YOU MUST PASS CS2002 AND ( PASS CS2001 OR PASS CS2101 )

Assessment pattern

100% Coursework

Re-assessment

Not applicable

Learning and teaching methods and delivery

Weekly contact

Full-time on placement.

Scheduled learning hours

0

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

50

The number of hours that students are expected to invest in independent study over the period of the module.