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CS352 Project Management for Computer Scientists

CS352 15 CATS (7.5 ECTS) Term 1

Availability

Core - CS MEng, CSE MEng; Option - CS, DM

Prerequisites

None.

Academic Aims

The aim of the module is to equip students with the knowledge required to manage technical projects through well established project management techniques.

Learning Outcomes

By the end of the module, students should:
▪ Appreciate the benefits effective project management
▪ Identify success criteria for a project, and evaluate the project against these.
▪ Understand the impact of risks, and be able to develop contingency plans to mitigate them effectively
▪ Be able to develop a project schedule
▪ Understand the construction of a project budget

Content

An understanding of robust project management techniques to include:
- Defining measurable project objectives
- Stakeholder identification and engagement
- Project planning and scheduling
- Budget management
- Efficient resource allocation
- Risk categorisation and mitigation
- Project evaluation

Books

  • The Mythical Man Month, Fred Brooks, Addison-Wesley, 1975
  • Project Management: A Systems Approach to Planning, Scheduling and Controlling, Harold Kerzner, Wiley, 2013
  • Agile Project Management: A Nuts and Bolts Guide to Success, Anthony Mersino, Vitality Chicago, 2015.

Assessment

Two-hour examination (80%)

Assessed work (20%)

Teaching

20 one-hour lectures plus 10 one-hour seminars


Jalote P, Fault Tolerance in Distributed Systems, Prentice Hall, 1994.
Lynch N, Distributed Algorithms, Morgan Kauffman, 1996.
Gouda M, Elements of Network Protocol Design, John Wiley, 1998.
  • Background: development and scope of social informatics; practical goals.
  • Understanding individual behaviour: perception, memory and action.
  • Modelling human interaction with digital systems.
  • Design methodologies and notations.
  • Techniques and technologies: dialogue styles, information visualisation.
  • Designer-user relations: iteration, prototyping.
  • Evaluation: formative and summative; performance and learnability.
  • Mobile computing and devices: novel interfaces; ubiquitous computing.
  • Organisational factors: understanding the workplace; resistance; dependability.
Innovation processes at scale: social shaping of IT, actor-network theory, co-production.