WBP-Data Processing & AI
Run by School of Computer Science and Electronic Engineering
20 Credits or 10 ECTS Credits
Semester 1 & 2
Overall aims and purpose
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.
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.
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.
Formulate a machine learning/data analysis/processing solution to the identified problem.
Apply theoretical aspects of data science and machine learning to a real business data-set/data problem.
Communcate the problem, method, solution and evaluation -- with references to the supporting materials -- to all interested parties.
Formal written report communicating the problem, its place within the literature and field, the work undertaken, results and an evaluation.
|LOGBOOK OR PORTFOLIO||Project Portfolio||
A set of experiments, inputs, and results of the project. This will include technical detail of the methods applied.
Present the work, in summary with appropriate detail where necessary, completed to tutors and peers.
Periodic progress reports, to be countersigned by the employer.
Teaching and Learning Strategy
Introductory and procedural lectures.
Supporting tutorials including on-site visits (where appropriate).
Private study, including individual assessment.
- 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
Subject specific skills
- 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
Courses including this module
Compulsory in courses:
- H116: BSc Applied Data Science (Degree Apprenticeship) year 3 (BSC/ADS)
- H300: BSc Applied Software Engineering (Degree Apprenticeship) year 3 (BSC/ASE)