CSC-10081 - Professional Practices in Data Science
Coordinator: Peter Wootton Tel: +44 1782 7 33767
Lecture Time: See Timetable...
Level: Level 4
Credits: 30
Study Hours: 300
School Office: 01782 733075

Programme/Approved Electives for 2025/26

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

Nil

Barred Combinations

None

Description for 2025/26

This module is designed to help you master the foundational and professional aspects of software and systems engineering, specifically as they apply to data science. You will learn how to evaluate digital services provided by service providers, ensuring you gather accurate requirements and adhere to professional standards. Additionally, this module will enhance your communication skills, study techniques, and report writing abilities.

Aims
This course aims to equip students with a comprehensive understanding of the principles and practices of professional software and systems engineering within the context of data science. It covers the essential aspects of requirements analysis, evaluation methodologies, and professional ethics. Additionally, the course focuses on developing students’ communication and study skills to ensure they are well-prepared for professional environments.

Intended Learning Outcomes

discuss the tenets of professional, legal and ethical practice involved in the sustainable exploitation of data science and computer technology: 1,2
demonstrate study and communication skills appropriate to professional software and data science: 1,2
explain how data science operates within the context of data governance (including the General Data Protection Regulation), data security, and communications: 1,2
debate general ethical concepts, such as deontological and teleological ethics and consider how they can be applied to data science and evaluate how AI related to aspects of Human rights and UN Sustainable Development Goals: 1,2
apply techniques associated with establishing the requirements and evaluation of requirements by seeking feedback from stakeholders: 2

Study hours

Active Learning 48 hours:
24 hours of lectures
12 hours group work sessions/ workshops (weekly team meetings required)
12 hours demo and team reviews
Independent Learning 252 hours:
122 hours individual coursework preparation (including contributing to the team presentation)
60 hours requirement evaluation of a case study
70 Independent study and skills development

School Rules

None

Description of Module Assessment

1: Portfolio weighted 60%
A portfolio of professional and ethical practice and reflective learning
Students will use appropriate study and communication skills to discuss and apply requirements gathering and evaluation techniques taught during the module to relevant case studies. They will also address professional, ethical, data governance, and security issues. The portfolio will include a case study on requirements evaluation and ethics, equivalent to a 2,000-word report.

2: Group Assessment weighted 40%
Group Project Report
The assessment is divided into two components: Written report (60%) and Group oral presentation (40%) An individual evaluation, equivalent to 800 words, will include: Reflection on your own contributions to the teamwork, Skills development Contributions of others in your team (peer review)and Reflection on the project work. For the group oral presentation, a pre-recorded presentation (e.g., a 15-minute video summarising the work done by the whole team for a data science-focused study) will be submitted. Additionally, weekly team working diaries must be submitted to Microsoft Teams, following a set template available in advance.