CSC-10050 - Module Specification
School of Computing and Mathematics
Faculty of Natural Sciences
For academic year: 2022/23 Last Updated: 19 January 2023
CSC-10050 - Requirements, Evaluation and Professionalism for Data Scientists
Coordinator: Nadia Kanwal Room: CR038
School Office: 01782 733075
Programme/Approved Electives for 2022/23
Available as a Free Standing Elective
Co-requisites
None
Prerequisites
None
Barred Combinations
None
Description for 2022/23
This module will enable students to understand the basis and practice of professional software and systems engineering, to understand the fundamentals of requirements, evaluation and professionalism, and to develop appropriate communication and study skills. Additionally, it will provide experience of producing a portfolio, working with case studies and report writing that will develop the skills required for producing the End Point Assessment portfolio.
Aims
To enable students to understand the basis and practice of professional software and systems engineering as applicable to data science; to understand the fundamentals of requirements, evaluation and professionalism; and to develop appropriate communication and study skills.
Intended Learning Outcomes
explain and apply techniques associated with establishing the requirements and evaluation of requirements by seeking feedback from stakeholders;: 1
discuss the tenets of professional, legal and ethical practice involved in the sustainable exploitation of data science and computer technology;: 1
apply study and communication skills appropriate to professional software, systems engineering and data science;: 1
explain how data science operates within the context of data governance (including the General Data Protection Regulation), data security, and communications.: 1
discuss the tenets of professional, legal and ethical practice involved in the sustainable exploitation of data science and computer technology;: 1
apply study and communication skills appropriate to professional software, systems engineering and data science;: 1
explain how data science operates within the context of data governance (including the General Data Protection Regulation), data security, and communications.: 1
Study hours
Lectures (delivered online) : 22 hours
Online and block release tutorials and practicals: 10 hours
Unsupervised coursework preparation: 40 hours
Self study: 78 hours
Online and block release tutorials and practicals: 10 hours
Unsupervised coursework preparation: 40 hours
Self study: 78 hours
School Rules
None
Description of Module Assessment
Portfolio submission including both report and professional skills component
Using appropriate study and communication skills, students will be asked to discuss and apply requirements gathering gathering and evaluation techniques taught during the module to a relevant case study and relate to professional, ethical, date governance and security issues. This will be the equivalent of a 3000-4000 word report.