Gwybodaeth am Coronafirws (Covid-19)

Modiwl ICE-2601:
Data Systems, Management & Eth

Ffeithiau’r Modiwl

Rhedir gan School of Computer Science and Electronic Engineering

20 Credyd neu 10 Credyd ECTS

Semester 2

Amcanion cyffredinol

The module aims to provide students with:

  • an awareness of the DIKW (Data, Information, Knowledge, Wisdom) pyramid.
  • understanding of classes of data and the processes that could be performed on it.
  • an appreciation of the ethical issues surround processing of data.
  • knowledge of the legal aspects when processing data.

Cynnwys cwrs

Indicative content includes:

  • Data; the definitions and concepts.
  • Contextualisation of data.
  • Analytical methods using data.
  • Ethics of processing data with and without automatic decisions.
  • Data Protection legislation (DPA, GDPR, HIPAA, COPPA, etc.).
  • Data collection mechanisms.
  • Storage mechanisms for data (in broad terms).

Meini Prawf

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.

Canlyniad dysgu

  1. Distinguish different classes of data.

  2. Discuss the role of data and analytics in the 'data economy'.

  3. Recognise potential legal and ethical consequences of collection, processing, and use of data.

  4. Examine appropriate methods to collect and store data.

Dulliau asesu

Math Enw Disgrifiad Pwysau
PRAWF DOSBARTH Class Test - Data Categories

Class Test focusing on types and categories of data.

25
PRAWF DOSBARTH Class Test - Analysis and Storage Ethics

Class test focusing on the ethics of using of data

25
ADDRODDIAD Data Collection and Analysis Proposal

A proposal detailing the collection method, storage and analysis of data for a given purpose.

50

Strategaeth addysgu a dysgu

Oriau
Lecture

Traditional lecture (1 hr x 12 weeks)

12
Tutorial

Tutorial for assistance with assessments (2 hrs x 12 weeks)

24
Private study

Private study, including completing assessments.

164

Sgiliau Trosglwyddadwy

  • 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
  • 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.
  • Dadl - Gallu cyflwyno, trafod a chyfiawnhau barn neu lwybr gweithredu, naill ai gydag unigolyn neu mewn grwˆp ehangach

Sgiliau pwnc penodol

  • Solve problems logically and systematically;
  • Appreciate the importance of designing products with due regard to good laboratory practice, health and safety considerations and ethical issues.
  • Use both verbal and written communication skills to different target audiences;
  • Demonstrate familiarity with relevant subject specific and general computer software packages.
  • Knowledge and understanding of facts, concepts, principles & theories
  • Use of such knowledge in modelling and design
  • Problem solving strategies
  • Deploy theory in design, implementation and evaluation of systems
  • Recognise legal, social, ethical & professional issues
  • Knowledge and understanding of commercial and economic issues
  • Evaluate systems in terms of quality and trade-offs
  • Development of general transferable skills
  • Methods, techniques and tools for information modelling, management and security
  • Specify, deploy, verify and maintain information systems
  • Knowledge and/or understanding of appropriate scientific and engineering principles
  • Knowledge and understanding of mathematical principles
  • Knowledge and understanding of computational modelling
  • Principles of appropriate supporting engineering and scientific disciplines

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