Run by School of Computer Science and Electronic Engineering

20.000 Credits or 10.000 ECTS Credits

Semester 1 & 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 visualisation skills to a problem within the student's employing organisation.

The exact content will vary by student and employer. The project will apply information visualisation to the problem identified and analysed in the first part of the project - ICL-3005.

excellent

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.

good

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.

threshold

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.

1. Apply theoretical aspects of data science and information visualisation to a real business data-set/data problem.

2. Formulate a visualisation suite to fit with the data analysis/processing solution found for the identified problem.

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

Type	Name	Description	Weight
	Project Portfolio		40.00
	Solution Write-up		40.00
	Presentation		10.00
	Progress Reports		10.00

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

• Literacy - Proficiency in reading and writing through a variety of media
• Numeracy - Proficiency in using numbers at appropriate levels of accuracy
• Computer Literacy - Proficiency in using a varied range of computer software
• Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
• Exploring - Able to investigate, research and consider alternatives
• Information retrieval - Able to access different and multiple sources of information
• Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
• Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
• Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
• Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
• Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
• Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

• 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

Compulsory in courses:

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