Programme/Approved Electives for 2024/25
None
Available as a Free Standing Elective
No
This module will enable students to understand the basics and practice professional aspects of software and systems engineering. It will help them evaluate the digital services provided by service providers for accurate requirements gathering and professionalism. Furthermore, It will help develop appropriate communication skills, study skills, and report writing.
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
discuss the tenets of professional, legal and ethical practice involved in the sustainable exploitation of data science and computer technology: 1,2demonstrate study and communication skills appropriate to professional software, systems engineering, and data science: 1,2explain how data science operates within the context of data governance (including the General Data Protection Regulation), data security, and communications: 1,2debate 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: 1,2apply techniques associated with establishing the requirements and evaluation of requirements by seeking feedback from stakeholders: 2
18 hours of lectures (a mix of synchronous and asynchronous teaching)22 hours of practical sessions (supported during block release; includes group work, writing group project reports and presentations, and making group oral presentations)120 hours on portfolio preparation140 hours on group projects, including group work, and preparing group project reports and presentations
Description of Module Assessment
1: Portfolio weighted 60%A portfolio of professional and ethical practice and reflective learning
2: Group Project weighted 40%Group Project Report