An honours degree (2.2 or better) in Computer Science

Teaching and Learning:
Lectures, tutorials, laboratory classes, seminars, group work, farm,
research project, individual independent study
Assessment Methods:
Written and oral examinations, tests, seminar, Presentations, mini-research projects, final year research
project report, continuous assessments
REGULATIONS
These regulations should be read in conjunction with the Faculty of Applied Science and the General Academic Regulations.
ENTRY QUALIFICATION
A student must have passed an (Hons) Degree (2.2 or better) in Computer Science.
DURATION
The Programme shall normally run over a period of eighteen (18) months for
full-time study.
When running on Block Release, the Programme shall be offered over a period of twenty-four (24) months.
MODE OF STUDY
Block Release
A student on Block Release shall normally be required to register for three (3) modules per Block. Stage I and Stage II shall each consist of two Blocks. Block II of Stage I and Block I of Stage II shall consist of two (2) modules and one (1) elective module each. Block II of Stage II shall consist of the Dissertation.
Full-time
A student on full-time is normally required to register for three (3) modules plus 1 elective per semester in Part I. Part II shall consist of the Dissertation. In order to proceed from Part I to Part II a student must pass all modules he/she would have registered for.
ASSESSMENT
A taught module shall be assessed by a three hour written examination at the
end of each semester. 6.2 The final grade in the module work shall be based on 25% from continuous
assessment and 75% from the final written examination. 6.3 To pass a module a student must obtain an overall mark of 50% from both
continuous assessment and the final written examination. 6.4 A student shall be expected to obtain a minimum of 50% in the Master’s
Thesis project work and 50% from Part I.
PROCEEDING TO THE NEXT PART
A student is expected to pass all his/her registered modules before proceeding to Part II.

SEMESTER I
SCS5107 Advanced Enterprise Architecture 24
Programming
SCS5110 Computational Discrete Mathematics 24
SCS5109 Advanced Database and Data Mining 24
(*Elective I refer below for list of electives)
SCS5205 Research Methods 24
SCS5208 Evolutionary Computing & Parallel 24
Distributed Processing
SEMESTER II
SCS5210 Simulation & Modelling 24
(*Elective I refer below for list of electives)

PART II
SEMESTER I
SCS 6200 Dissertation 110

List of electives
The student is expected to choose one module per semester
Electives I
SCS 5103 Pattern Recognition & Image Processing
SCS 5111 Interactive Computer Graphics
SCS 5112 Ontology Engineering
Electives II
SCS 5205 Software Methodology
SCS 5211 Digital Signals Processing

PART I
SCS 5107 Enterprise Architecture Programming 24 Credits
The module has an introduction to application server programming and business logic programming; Transaction processing, concurrency control, Event-driven programming, asynchronous method invocation, job scheduling, Inter process communication; Deployment of software components in an application server; Business Interface development and deployment.
SCS 5109 Advanced Database And Data Mining 24 Credits
The module looks at Data Models; The Enhanced Entity Relationship (EER) Model, EER Models to Relational Databases, Database Design and Implementation; design methodologies, implementation methodologies, Physical Database design and Tuning, Query processing and Optimization; Algorithms for Query Processing and Optimization, Transaction Processing, Concurrency Control Techniques; Database Security and Distribution, Distributed Databases, Mobile Databases Machine Learning and Pattern Recognition and Data Mining.
SCS 5110 Computational Discrete Mathematics 24 Credits
The module explores Discrete models; Foundations; Basic concepts of sets and functions; Finite series; Logic; Propositional logic; Predicate logic; Combinational circuits; Induction; Finite probability space, events; Conditional probability, Bayes’ theorem; Integer random variables; Expectations; Variance Analysis and verification; Searching algorithms; Recursive algorithms; Relations; Basic concepts; Properties of relations; Operations on relations; Undirected graph, Directed graph, weighted graph, Euler circuits and Hamiltonian cycles; Graph isomorphism and representations; Planar graphs; Trees; Different state machines; Input, Output, Initial state and Transition table.
SCIS 5205 Research Methods 24 Credits
The module looks at Research, research types, Research planning and design, Project Proposal, Data collection techniques, Literature review, Research techniques, Methodology and Methods, Sampling techniques, Validity and reliability, Research report writing and Ethical issues in Information Systems Research.
SCS 5208 Evolutionary Computing And Parallel Distributed Processing 24 Credits
The module examines fundamentals of genetic algorithms, genetic programming; Conceptual simplicity and broad applicability of genetic algorithms; Features of evolutionary computation, evolutionary strategies, evolutionary programming; Hybridization and Optimization techniques; Heuristic level: knowledge representation, inference strategies; Man-machine interfaces; Fuzzy set theory; Decision: Classical, nonstandard and fuzzy logic; Data representation; Network configurations: single layer non-recurrent networks; Multilayer non-recurrent networks; Recurrent networks; Application for artificial neural networks:
character and speech recognition, image analysis Parallel distributed processing; General framework; Distributed representation; Basic mechanisms and formal analysis.
SCS 5210 Simulation And Modelling 24 Credits
The module looks at advances in simulation and modelling methodology; All students are expected to have completed an introductory module in simulation; Modelling complexities and decision-making simulation using system dynamics; Applied statistical functions, Experimentation, Applied statistical methods for analysis and modelling; Approaches to structuring simulations; Contrasting discrete, continuous and agent-based simulation.
PART II
SCS 6201 Dissertation 110 Credits
ELECTIVES
SCS5103 Pattern Recognition And Image Processing 24 Credits
The module is an introduction to pattern recognition; Fundamental problems in pattern recognition; Foundations of pattern recognition algorithms and machines, including statistical and structural methods; Data structures for pattern representation, feature discovery and selection, classification vs; description, parametric and non-parametric classification, supervised and unsupervised learning, use of contextual evidence, clustering, recognition with strings, and small sample-size problems biological object recognition and the Bayesian decision theory;
SCS 5205 Software Methodology 24 Credits
The module is an overview of Software Engineering, the Software Development Process; requirements analysis and specification phase Design phase; implementation phase, maintenance; Engineering with a Programming Language; Software Engineering Paradigms; Engineering with existing software and Software Engineering Project;
SCS 5111 Interactive Computer Graphics 24 Credits
The module explores the fundamentals of Computer Graphics: Structure of Images; Image formats, compression and dithering; Mesh Data Structures; shapes as vertices, edges and faces, using the indexed face set and the half-edge data structures; Transformational Geometry: Scale, rotation, translation, stretch and shear of a shape; Viewing; Perspective, the illusion of depth; Lighting; Rasterisation, convert mesh triangles to screen pixels; Texture Mapping; Visibility; GPU Programming; Colour Theory; Physical Simulation Animation; Parametric Surfaces; Implicit Surfaces; Quaternion Rotations; Skinning and shadowing.
SCS 5112 Ontology Engineering 24 Credits
The module looks at ontology, Types of ontologies; An ontology engineering for the Semantic Web; Notion of ontology technology, Ontology Web Language to represent ontologies and basic aspects to develop ontologies; Top-down Ontology design and foundational ontologies and bottom-up design using non-ontological resources such as
relational databases, natural language or thesauri and fundamental aspects of methods and methodologies and Application of ontology technologies.
SCS 5211 Digital Signals Processing 24 Credits
This module explores signals and their functional representations; Basics of Counting: Counting arguments (Set cardinality and counting; Sum and product rule); cross-reference AR/Digital logic and digital systems, Computer representation of data (Bits; bytes and words), Numeric data representation and number bases; Fixed- and floating-point systems; Signed and twos-complement representations; Representation of non-numeric data (character codes, graphical data); Representation of records and arrays, digital systems (Combinational vs; sequential logic), State Machines (Digital vs; Analogue and Discrete vs; Continuous Systems), Simple logic gates, Parallelism, synchronization, Multimedia Systems, Principles of digital forensics: Digitization (storage, interchange, digital objects, composites, and packages). The module has been aligned to the ACM/IEE curriculum. The topics that dealt with theoretical aspects of digital computer signal processing have been reviewed to reflect a solid approach rather than an abstract approach.