Rhedir gan School of Computer Science and Electronic Engineering

20.000 Credyd neu 10.000 Credyd ECTS

Semester 1

Trefnydd: Dr Ik Soo Lim

This module aims to introduce concepts of fundamental data structures and algorithms. It will also introduce methods to analyse algorithms for complexity both in time and space, and the required mathematics.

Indicative content includes:

• Data structures and abstract data types; arrays, linked-lists, stacks, queues, sets and binary search trees.
• Algorithms: sorting, insertion, deletion, searching, iterative and recursive algorithms.
• Mathematics: powers, exponentials, logarithms, series summations, recurrences, sets and Venn diagrams.
• Efficiency measures for time and space: rates of growth, asymptotic behaviour, and big-O notation.

da

Equivalent to the range 60%-69%. Is able to analyse a task or problem to decide which aspects of theory and knowledge to apply. Solutions are of a workable quality, demonstrating understanding of underlying principles. Major themes can be linked appropriately but may not be able to extend this to individual aspects. Outputs are readily understood, with an appropriate structure but may lack sophistication.

trothwy

Equivalent to 50%. Uses key areas of theory or knowledge to meet the Learning Outcomes of the module. Is able to formulate an appropriate solution to accurately solve tasks and questions. Can identify individual aspects, but lacks an awareness of links between them and the wider contexts. Outputs can be understood, but lack structure and/or coherence.

ardderchog

Equivalent to the range 70%+. Assemble critically evaluated, relevent areas of knowledge and theory to constuct professional-level solutions to tasks and questions presented. Is able to cross-link themes and aspects to draw considered conclusions. Presents outputs in a cohesive, accurate, and efficient manner.

1. Describe the concepts of fundamental data structures and algorithms.

2. Evaluate algorithms, in terms of efficiency, using complexity theory.

Math	Enw	Disgrifiad	Pwysau
	Examination		60.00
	Assignment 1		10.00
	Assignment 2		10.00
	Assignment 3		20.00

		Oriau
Private study	Revision of lecture notes.	56
Work-based learning	ASSESSED assignments based on computer programming.	120
Lecture	Interactions via questions-and-answers.	24

• Rhifedd - Medrusrwydd wrth ddefnyddio rhifau ar lefelau priodol o gywirdeb
• Defnyddio cyfrifiaduron - Medrusrwydd wrth ddefnyddio ystod o feddalwedd cyfrifiadurol
• Hunanreolaeth - Gallu gweithio mewn ffordd effeithlon, prydlon a threfnus. Gallu edrych ar ganlyniadau tasgau a digwyddiadau, a barnu lefelau o ansawdd a phwysigrwydd
• Archwilio - Gallu ymchwilio ac ystyried dewisiadau eraill
• Adalw gwybodaeth - Gallu mynd at wahanol ac amrywiol ffynonellau gwybodaeth
• Dadansoddi Beirniadol & Datrys Problem - Gallu dadelfennu a dadansoddi problemau neu sefyllfaoedd cymhleth. Gallu canfod atebion i broblemau drwy ddadansoddiadau ac archwilio posibiliadau
• Dadl - Gallu cyflwyno, trafod a chyfiawnhau barn neu lwybr gweithredu, naill ai gydag unigolyn neu mewn grwˆp ehangach
• Hunanymwybyddiaeth & Ystyried - Bod yn ymwybodol o'ch cryfderau, gwendidau, nodau ac amcanion eich hun. Gallu adolygu ,cloriannu a myfyrio'n rheolaidd ar eich perfformiad eich hun ac eraill.

• Apply an understanding and appreciation of continuous improvement techniques
• Solve problems logically and systematically;
• Analyse and display data using appropriate methods and mathematical techniques;
• Knowledge and understanding of facts, concepts, principles & theories
• Problem solving strategies
• Knowledge and understanding of mathematical principles

Rhestrau Darllen Bangor (Talis)

http://readinglists.bangor.ac.uk/modules/ice-4201.html

Rhestr ddarllen

Main Course text: Java collections: an introduction to abstract data types, data structures, and algorithms - David A. Watt, Deryck F. Brown c2001

Highly Recommended: Introduction to algorithms - Thomas H. Cormen 2010, c2009

Opsiynol mewn cyrsiau:

• G5BC: MSc Computing for Data Science year 1 (MSC/CDS)
• G5BA: MSc Computing year 1 (MSC/COMP)