Introductory description

FP016-30 Computer Science

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: Algorithms and Computational Thinking
Introduction to Computer Science
Computational Thinking
Algorithms for Searching and Sorting
Data Structures

Part 2: Python Programming
What is a computer program?
Python Programming Language
Variables and Data Types
Selection
Repetition
Functions & Recursion
Development Environments
Individual Python Programming Project (30%)

Part 3: Data Representation
Numbers and Number Systems
Data Representation and Transformation
Real Numbers

Part 4: Computer Systems and architecture
Computer Logic
Hardware and Components
Operating Systems
Communication and Networks
Machine Code
Boolean Mathematics
Boolean Circuit Design
Binary and Bit Manipulation
Data Integrity

Part 5: Ethics and Consequences
Data Security and Privacy
Ethics of Computing
Consequences of Computing Group Presentation (10%)

Part 6: Software Engineering and Business
Computing in Business and Society
Top-Down Design & Specification
Implementation & Testing
Deployment & Maintenance

Page 7: Object Orientated Paradigm
OOP Languages (python)
Classes
Encapsulation
Inheritance
Polymorphism

Learning outcomes

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

• Recognise and show understanding of specific computing terminology, technology, key developments, principles and methods;
• Apply computational thinking to translate a range of problems into a form that can be solved by the computer;
• Use a combination of practical programming skills and theoretical knowledge to solve calculations, manipulate data and predict outcomes;
• Show an appreciation of 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
• Present and disseminate computing concepts, solutions and results including the necessary evidence to a range of audiences.

Indicative reading list

Dale, N and Lewis, J. (2015) Computer Science Illuminated (6th ed.) Jones and Bartlett Burdett, A. et al. (2013) BCS Glossary of Computing and ICT (13th ed.) BCS, The Chartered Institute for IT Brookshear, G and Brylow, D (2014) Computer Science: An Overview (12th ed) Pearson Shaw, Z (2017) Learn Python 3 the Hard Way. Addison-Wesley
Python Crash Course. Eric Matthes(2019) Introduction to Algorithms, 3rd Edition (The MIT Press) 3rd Edition

Interdisciplinary

Interdisciplinary links with mathematics.

Subject specific skills

To develop students use of analysis to interpret and critique existing historiographical debates and draw their own conclusions from the examination of primary sources.

Transferable skills

No transferable skills defined for this module.