CS104 – Information & Information Systems

Credits 20
Level SHE Level 1
Prerequisites None
Availability Semesters 1 and 2
Elective Yes
Contact 44 lectures and 20 two-hour practicals over two semesters
Assessment 30% classwork, 70% written exam, with possibility of exam exemption
Lecturer Dr David Bevan | Dr Dmitri Roussinov

Aims and Objectives

To help students understand a broad knowledge of information systems and how information is created, used and disseminated within an information society.

Learning Outcomes

On completion of this class, a student should be able:

  1. To understand what is meant by an information system.
  2. To demonstrate a broad understanding of the technology underlying information systems, and in particular those information systems which have a deep impact on society.
  3. To understand techniques for information and knowledge representation.
  4. To understand key issues in information creation, sharing and dissemination.
  5. To understand methods of information security and protection.
  6. To evaluate the success of an information system with respect to determined criteria for success.
  7. To understand the design principles behind successful information systems such as Google or Amazon.
  8. To appreciate the activities for the organization and processing of information that take place behind the scene to make digital information accessible to the users.
  9. To understand how information can be protected through password control and encryption.
  10. To understand how novel information security techniques such as facial recognition and biometric control operate.
  11. To understand common vulnerabilities and types of malicious programs.
  12. To understand how to design a secure system.


The class will take a “how it works” approach, including a significant amount of hands-on practical experience, on the theory and practice underlying the storage, presentation and access of information in the context of the World-Wide Web and large-scale information systems.

  1. Introduction to information systems: an introduction to the concepts behind different classes of information systems; introductions to large scale information processing, social information systems, and information organisation; an introduction to how information systems can be evaluated with respect to end-user tasks.
  2. Information representation: an introduction to information theory, including data formats, error detection and correction, data compression, and what it means to measure information.
  3. Information use: an introduction into using information by modern systems in various applications such as computer vision, game playing, web search and natural language processing.
  4. Information analysis: an introduction into algorithms that can analyse data such as machine learning, classification, optimization, derivatives, gradients and linear algebra.
  5. Information security: an introduction to information security, particularly for interactive information systems; encryption, password creation and control, biometric information security, vulnerabilities, malicious programs, WiFi security, secure designs and the basics of penetration testing.

Assessment and Exemption

The class will consist of four modules, each of which will have an associated class test. The class test for each module will contribute 25% of the coursework mark. Students who achieve a pass more (i.e. more than 40%) in all four of the module assignments and an average of 60% or over will be exempted from the degree examination. The mark returned for a student who is exempt will be the average mark gained on the four modules.


The resit for the class will take the form of a 2 hour examination. The resit examination will be designed to test all aspects of the course including practical elements. The mark returned for the resit attempt will be based on the resit examination alone.

Indicative Reading*

* This list is indicative only – the class lecturer may recommend alternative reading material. Please do not purchase any of the reading material listed below until you have confirmed with the class lecturer that it will be used for this class.

James V. Stone, Information Theory: A Tutorial Introduction, Sebtel Press, 2015.

Alexander Nakhimovsky and Tom Myers. Google, Amazon, and beyond: creating and consuming web services. Apress. 2004.

Sergio Verdu and Steven W. McLaughlin (eds.). Information theory: 50 years of discovery. IEEE Press. 2000.

Yann LeCun, Yoshua Bengio & Geoffrey Hinton. Deep learning. Nature, volume 521, pages 436–444 (28 May 2015).