Introductory description

FP016-30 Computer Science:
This module combines the theory of computing and practical activities to familiarise the student with the computer science field.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Part 1: Computer Architecture:
Computer Logic and Binary System.
Boolean Mathematics.
Boolean Circuit Design.
Computer Architectures.
Real Numbers.

Part 2: Computational Thinking and Python Programming:
Computational and Logical Thinking.
Python Programming Language.
Variables and Data Types.
Control flow structures: conditional and repetition.
Functions & Recursion.
Classes.
Python Programming Project.

Part 3: Ethics and Consequences:
Ethics of Computing: Data Security and Privacy.
Ethical, social and legal issues behind Computing Technologies Presentation.

Part 4: Computer Systems:
Hardware and Components.
Operating Systems.
Communication and Networks.
Data Transmission.

Part 5: Software Engineering and Business:
Introduction to Software Engineering.
Top-Down Design & Specification.
Implementation & Testing.
Deployment methodologies.

Part 6: Data Representation and Algorithms:
Numbers and Number Systems.
Data Representation and Transformation.
Algorithms for Searching and Sorting.
Data Structures.

Page 7: Object-Orientated Paradigm:
OOP Languages (Python).
Encapsulation.
Inheritance.
Polymorphism.

Learning outcomes

By the end of the module, students should be able to:

• Recognise and explain specific computing terminology, technology, key developments, principles and methods;
• Apply computational thinking to translate a range of problems into computer-based solutions;
• Use a combination of practical programming skills and theoretical knowledge to solve calculations, manipulate data and predict outcomes;
• Identify and describe the social, legal and ethical consequences of computer applications and technology;
• Display professional software engineering skills such as team working, time management and the importance of commercial reality; and
• Explain computing concepts, solutions and results to a range of audiences.

Indicative reading list

-> Dale, Nell, and John Lewis. Computer Science Illuminated, Jones & Bartlett Learning, LLC, 2019.

-> Floyd, Thomas. Digital Fundamentals, Global Edition, Pearson Education, Limited, 2015.

-> Karl Beecher. Computational Thinking : A Beginner’s Guide to Problem-Solving and Programming. BCS, The Chartered Institute for IT, 2017.

-> Matthes, Eric. Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming, No Starch Press, 2019.

-> Rob Mastrodomenico. The Python Book. Wiley, 2022.

-> Shaw, Zed A. Learn Python the hard way: a very simple introduction to the terrifyingly beautiful world of computers and code. Pearson Addison Wesley, 2017.

-> Brookshear, J., et al. Computer Science: an Overview, Global Edition, Pearson Education, Limited, 2019.

-> Halsall, Fred. Introduction to data communications and computer networks. Electronic systems engineering series, 1985.

-> Thomas H. Cormen. Introduction to algorithms. 3rd ed. Massachusetts Institute of Technology, 2009. ISBN 978-0-262-03384-8.

View reading list on Talis Aspire

Interdisciplinary

The Ethics Presentation (Summative assessment) includes research skills learned at EAP and IRS, such as academic citation and referencing.
Interdisciplinary links with mathematics.

Subject specific skills

Students will be able to:

• interpret, analyse and explain computing principles and methods;
• lead debates and draw conclusions from examining primary sources;
• Develop computer-based solutions for a range of problems using software engineering skills.

Transferable skills

Communication and presentation skills;
Collaboration and group work skills;
Research skills;
Critical thinking.