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Comments about BSc Computer Science - At the institution - Sheffield - South Yorkshire
Objectives
Students are taught to understand the theoretical principles underlying a problem, and to be able to engineer a solution. Students are also led to a real understanding of the practical issues involved in the development of reliable and effective software systems in a business or industrial context.
Entry requirements
-GCE/VCE A Levels - ABB including A Level Mathematics -BTEC National Certificate: 2 Distinctions and Grade B in A Level Mathematics -Two GCE A Levels plus two GCE AS Levels - AB+BB including A Level Mathematics -Scottish Highers: AAAB including Mathematics -Scottish Advanced Highers: ABB including Mathematics -Irish Leaving Cert. - AABBB including Mathematics -International Baccalaureate - 33 points including 5 points in Mathematics at Higher Level
Academic title
Computer Science BSc
Course description
This is a list of modules that have been offered in the past. We expect similar modules to be offered for courses starting in 2009.
Typical First Year Modules
Module/Unit
-Artificial Intelligence Techniques
-Computer Architectures
-Continuous Foundations
-Discrete Foundations
-Introduction to Artificial Intelligence
-Introduction to Programming
-Network Architectures
-Object-Oriented Programming
-Requirements Engineering
-Systems Design and Testing
Typical Second Year Modules
Module/Unit
-Software Hut 20
-Abstract Data Types
-Adaptive Robotics
-Database Technology
-Functional Programming
-Human Computer Interaction and Graphical Interfaces
-Machines and Languages
-Pattern Processing
-Professional Issues
-Symbolic Reasoning
-Systems Analysis and Design
Typical Third Year Modules
Module/Unit
-Individual Research Project 2
-Individual Research Project 1: Survey and Analysis Report
-3D Computer Graphics
-Adaptive Intelligence
-Advanced Software Engineering Seminars
-Applications of Information Theory
-Computer Games Technology
-Concurrent Systems
-Critical Analysis in Artificial Intelligence
-Java E-Commerce
-Machine Learning Foundations
-Modelling and Simulation of Natural Systems
-Natural Language Processing
-Network Performance Analysis
-Programming Language Semantics
-Software Measurement and Testing
-Speech Processing
-Speech Technology
-Text Processing
-The Intelligent Web
-Theory of Distributed Systems