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ME52079: Digital transformation: project and change management

[Page last updated: 16 August 2024]

Academic Year: 2024/25
Owning Department/School: Department of Mechanical Engineering
Credits: 10 [equivalent to 20 CATS credits]
Notional Study Hours: 200
Level: Masters UG & PG (FHEQ level 7)
Period:
Academic Year
Assessment Summary: CWRI 70%, CWVG 30%
Assessment Detail:
  • Digital transformation group presentation (CWVG 30%)
  • Digital transformation report (CWRI 70%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites:
Learning Outcomes: Critically assess project planning techniques and tools for digital transformation
Envision how AI can be used to support project and change management
Examine theoretical models and practical strategies for project and change management
Recognise and discuss the ethical implications of AI in project management and change management.


Synopsis: Explore how project and organisational change management enable digital transformation. You'll learn fundamental theoretical models and practical strategies in project and change management. You'll discover how AI can support at all stages of managing an engineering project, while considering any ethical implications. A combination of theoretical learning and practical sessions will help you develop the skills and knowledge needed to excel in this evolving field.

Aims: Explore how AI is impacting project planning and execution and explore strategies for managing and leading change. Through a combination of theoretical learning and practical sessions, you will develop the knowledge and skills necessary to excel in the rapidly evolving field of AI-supported project management and explore factors such as strategic management, contemporary engineering and design practices and organisational factors.

Skills: Project and change management, quality assurance and monitoring, leading change

Content: Introduction to project and change management
Project initiation and stakeholder analysis
Project planning and scheduling for AI-supported engineering projects
Quality assurance and monitoring for AI-supported engineering projects
Leading change in AI-enhanced projects
The role of AI in supporting project management.

Course availability:

ME52079 is a Must Pass Unit on the following courses:

Department of Electronic & Electrical Engineering
  • TEEE-AFM22 : MSc Artificial Intelligence for Engineering and Design
  • TEEE-AWM22 : MSc Artificial Intelligence for Engineering and Design

Notes:

  • This unit catalogue is applicable for the 2024/25 academic year only. Students continuing their studies into 2025/26 and beyond should not assume that this unit will be available in future years in the format displayed here for 2024/25.
  • Courses and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.