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PO Domains
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Programme Learning Outcome
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PO1
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Knowledge - Breadth
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Demonstrate comprehensive and systematic understanding of the facts, principles, theories and methods from the fields of Mathematics, Statistics, Computer Science and Business Intelligence which are relevant to the Data Analyst.
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PO2
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Knowledge - Breadth
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Identify and articulate the key considerations of a “Big Data” problem; draw complex information together; critically comment on the technical, social, economic, environmental and political implications of own work and the work of others in Data Science, including an appreciation of the philosophical and ethical issues involved.
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PO3
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Knowledge - Kind
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Demonstrate comprehensive knowledge and detailed understanding of: the theories, paradigms, defining concepts and underlying principles of the rapidly evolving Data Science and Analytics field; demonstrate knowledge and experience of advanced and new methods and technologies for acquiring, interpreting and analysing big data, with a critical awareness of the appropriate contexts for their use through the study of original papers, reports, journals, and data sets; demonstrate comprehensive knowledge and understanding of: the identification, definition and resolution of novel, complex research problems; relevant legal and regulatory frameworks; aspects of the defining elements and the inter-relationships of Data Science & Analytics as a result of in-depth study and research; demonstrate comprehensive knowledge and appreciation of the current limits of theoretical and applied knowledge in interdisciplinary field of Data Science and Analytics.
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PO4
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Skill - Range
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Demonstrate mastery of standard and specialised research tools in Statistics, Mathematics, Computer Science and Business Intelligence; use these to proactively model, troubleshoot and solve original technical problems in the “Big Data” space; source relevant information, critically interpret and apply appropriate referenced literature from a wide range of information sources; maintain detailed records of activities; present and defend scientific research findings in a variety of forms to data scientists, “data savvy” practitioners, and non-specialists; formulate a hypothesis and design a relevant programme of investigation; work independently within defined time and resource boundaries; write accurately and in a manner consistent with scientific publications in Data Science or related disciplines.
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PO5
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Skill - Selectivity
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Design, develop and test novel hypotheses; design experiments; select from a range of scientific skills, in particular those which draw from Mathematics/Statistics and Computer Science, so as to apply the most appropriate in a range of situations; think independently and make informed effective decisions; make decisions in the Data Science work setting; develop new skills either independently or with minimal mentoring.
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PO6
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Competence - Context
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Apply advanced research skills and Big Data technologies; act autonomously and think independently; constructively criticise, draw conclusions and offer recommendations in a wide range of contexts, including unpredictable situations; formulate and communicate judgements, with incomplete or limited information.
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PO7
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Competence - Role
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Act effectively, demonstrate initiative, lead and take responsibility in a complex interdisciplinary team environment with data scientists and qualified practitioners of other disciplines; develop and implement novel technical solutions for “Big Data” problems; reflect on own practices.
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PO8
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Competence - Learning to Learn
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Learn to act in variable and unfamiliar learning contexts; identify knowledge gaps through effective self-evaluation; source and undertake self-learning as necessary for continued academic and professional self-development as a Data Scientist.
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PO9
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Competence - Insight
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Identify and articulate the key considerations of a “Big Data” problem; draw complex information together; critically comment on the technical, social, economic, environmental and political implications of own work and the work of others in Data Science, including an appreciation of the philosophical and ethical issues involved.
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