CSC-10078 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

Programme/Approved Electives for 2024/25

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2024/25

This module offers the opportunity to develop and showcase critical data science knowledge, skills, and behaviors through workplace projects. You will learn to apply data science principles in organizational contexts, apply governance, security, bias, ethics, and compliance, and handle real-world data patterns for decision-making. You¿ll also hone your abilities to communicate effectively with diverse audiences, using appropriate support materials and visualizations, and build collaborative relationships at strategic and operational levels

This module aims to equip you with the ability to learn independently and effectively apply your skills and knowledge in the workplace. Spanning three semesters, it combines work-related and hands-on learning activities. We enhance your learning experience through active social learning, leveraging digital platforms like KLE and MS Teams. This approach fosters flexibility and responsiveness to your individual learning and study needs.
Clear expectations will be set for your engagement, and regular consultation hours will be provided with your supervisors. The module's assessment components prepare you for the End Point Assessment at the end of the apprenticeship program. This includes workplace projects and knowledge test,

Intended Learning Outcomes

Apply knowledge, skills, and behaviors of a professional data scientist in a real-work environment to achieve real-work objectives.
: 2,3
Analyze and execute a work-based data science project, demonstrating the skills and behaviors needed for planning, including an evaluation of processes followed, and synthesize recommendations for future activities.: 2,3
Evaluate understanding of basic mathematics, statistics, ethics, security, and governance relevant for data scientists: 1

Study hours

Active learning: 36 hours
Independent learning and meeting with supervisors: 64
Working on workplace project: 150 hours
Report writing: 50 hours

School Rules

None

Description of Module Assessment