Rhedir gan School of Computer Science and Electronic Engineering

20.000 Credyd neu 10.000 Credyd ECTS

Semester 1 a 2

This module aims to allow the student to put into practice the theory and skills gained over the course of their programme. This will apply the data science and machine learning skills to a problem within the student's employing organisation.

The exact content will vary by student and employer. The project will apply data processing, machine learning and AI techniques to an industrial problem and data set.

trothwy

Equivalent to 40%. 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.

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.

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. Formulate a machine learning/data analysis/processing solution to the identified problem.

2. Apply theoretical aspects of data science and machine learning to a real business data-set/data problem.

3. Communcate the problem, method, solution and evaluation -- with references to the supporting materials -- to all interested parties.

Math	Enw	Disgrifiad	Pwysau
	Project Portfolio		40.00
	Solution Write-up		40.00
	Presentation		10.00
	Progress Reports		10.00

		Oriau
Lecture	Introductory and procedural lectures.	4
Tutorial	Supporting tutorials including on-site visits (where appropriate).	12
Private study	Private study, including individual assessment.	184

• Llythrennedd - Medrusrwydd mewn darllen ac ysgrifennu drwy amrywiaeth o gyfryngau
• 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
• Sgiliau Rhyngbersonol - Gallu gofyn cwestiynau, gwrando'n astud ar atebion a'u harchwilio
• Dadansoddi Beirniadol & Datrys Problem - Gallu dadelfennu a dadansoddi problemau neu sefyllfaoedd cymhleth. Gallu canfod atebion i broblemau drwy ddadansoddiadau ac archwilio posibiliadau
• Cyflwyniad - Gallu cyflwyno gwybodaeth ac esboniadau yn glir i gynulleidfa. Trwy gyfryngau ysgrifenedig neu ar lafar yn glir a hyderus.
• Gwaith Tîm - Gallu cydweithio'n adeiladol ag eraill ar dasg gyffredin, ac/neu fod yn rhan o dîm gweithio o ddydd i ddydd
• 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.

• Knowledge and understanding of facts, concepts, principles & theories
• Use of such knowledge in modelling and design
• Problem solving strategies
• Analyse if/how a system meets current and future requirements
• Deploy theory in design, implementation and evaluation of systems
• Recognise legal, social, ethical & professional issues
• Knowledge and understanding of commercial and economic issues
• Knowledge of management techniques to achieve objectives
• Knowledge of information security issues
• Specify, design or construct computer-based systems
• Evaluate systems in terms of quality and trade-offs
• Recognise risk/safety for safe operation of computing equipment
• Deploy tools effectively
• Work as a member of a development team
• Development of general transferable skills
• Deploy systems to meet business goals
• Methods, techniques and tools for information modelling, management and security
• Knowledge of systems architecture
• Specify, deploy, verify and maintain information systems
• Defining problems, managing design process and evaluating outcomes
• System Design
• Knowledge and/or understanding of appropriate scientific and engineering principles
• Knowledge and understanding of mathematical principles
• Knowledge and understanding of computational modelling
• Specify, deploy, verify and maintain computer-based systems
• Principles of appropriate supporting engineering and scientific disciplines

Gorfodol mewn cyrsiau:

• H116: BSc Applied Data Science (Degree Apprenticeship) year 3 (BSC/ADS)
• H120: BSc Applied Data Science (Degree Apprentice - Coleg Cambria) year 3 (BSC/ADSC)