Visualisation and Graphical Algorithms
Rhedir gan School of Computer Science and Electronic Engineering
20.000 Credyd neu 10.000 Credyd ECTS
Semester 1 a 2
Displaying analytical data can be important to communicating the correct information. Taking data and then visualising this to show deeper analysis requires an understanding of the underlying algorithms and being able to code this visually.
This module will provide learners with the ability to visualise graphical data by using advanced algorithms. The students will build on an earlier Digital Graphics module and learn how to delve deeper into their own analysis and how to represent this in a clear visual manner.
Indicative content includes:
- Understand the nature of analytical data
- Understand the visualisation process of data
- Use and understand a range of Java Script elements
- Understand how to use the HTML Canvas to display algorithmic data
- How to draw more precise elements using html Canvas and Java Script
- Manipulation of images (Masks, Brightness, Colour, Effects) to highlight data
- Simple animation based on data (predict forecast, show growth/loss etc.)
- Interpreting a business scenario to create a professional visualisation.
- Review and justify visualisation and development decisions made.
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.
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.
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.
Produce visual representations for a set of supplied data using Canvas and Java Script in a suitable visual form.
Justify the visual representation choices made.
Analyse an informative scenario and create a set (or sets) of meaningful data.
Display a meaningful representation of analysed data using visual tools such as Canvas and Java Script.
Review the completed solution.
Strategaeth addysgu a dysgu
The tutor directed student learning will be supported by online learning materials hosted or signposted on the VLE.
The classroom-based element will include student-centred learning methods such as interactive lectures, case studies, group discussions and practical workshops.
- 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
- Dadansoddi Beirniadol & Datrys Problem - Gallu dadelfennu a dadansoddi problemau neu sefyllfaoedd cymhleth. Gallu canfod atebion i broblemau drwy ddadansoddiadau ac archwilio posibiliadau
Sgiliau pwnc penodol
- 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
- Specify, design or construct computer-based systems
- Evaluate systems in terms of quality and trade-offs
- Deploy tools effectively
- Development of general transferable skills
- Deploy systems to meet business goals
- Methods, techniques and tools for information modelling, management and security
- Specify, deploy, verify and maintain information systems
- 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
Rhestrau Darllen Bangor (Talis)http://readinglists.bangor.ac.uk/modules/icl-2011.html
Spiegelhalter , D., 2019. The Art of Statistics: Learning from Data. Pelican Books.
Williams, A., 2017. Data Analytics for Beginners: Introduction to Data Analytics. CreateSpace Independent Publishing Platform
Geary, D., 2012. Core HTML5 Canvas: Graphics, Animation, and Game Development. Prentice Hall
Cyrsiau sy’n cynnwys y modiwl hwn
Gorfodol mewn cyrsiau:
- H116: BSc Applied Data Science (Degree Apprenticeship) year 2 (BSC/ADS)
- H120: BSc Applied Data Science (Degree Apprentice - Coleg Cambria) year 2 (BSC/ADSC)