MARC

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022 |a 2049-0968 
022 |a 2049-0976 
035 |a 3161970820 
045 2 |b d20240701  |b d20240731 
084 |a 183535  |2 nlm 
100 1 |a Lu, Jing  |u University of Winchester, UK 
245 1 |a Data Scientist Knowledge and Skills Evaluation Towards a Data-Driven Research Methodology 
260 |b Academic Conferences International Limited  |c Jul 2024 
513 |a Conference Proceedings 
520 3 |a The modern business world increasingly requires a higher level of data science expertise as well as abilities in problem solving and data analytics. Data science is a broad and fast-moving field of methods, processes, algorithms and systems to extract insights from data. The University of Winchester has followed the guidance of the Institute for Apprenticeships and Technical Education (IfATE) and worked in partnership with a number of international, national and regional employers in the design and development of its Data Scientist (integrated degree) programme, which leads to a Bachelor's degree in Data Science. This degree apprenticeship supports students in gaining the knowledge and skills that are in demand by employers today and into the future, where working in multi-disciplinary teams alongside domain experts will often be the norm. IfATE specifies an End-point Assessment (EPA) plan to enable the apprenticeship to be completed in accordance with its Data Scientist degree apprenticeship standard. This paper considers professional practice and competence in data science and links the processes used in completing the EPA with domain-based knowledge and expertise. It reviews representative solution methodologies before demonstrating the applicability of a data-driven research methodology to discover insights and achieve organisational goals. 
610 4 |a University of Winchester Environmental Protection Agency--EPA 
653 |a Problem solving 
653 |a Scientists 
653 |a Collaboration 
653 |a Hypothesis testing 
653 |a Curricula 
653 |a Professional practice 
653 |a Data analysis 
653 |a Data science 
653 |a Employers 
653 |a Apprenticeship 
653 |a Skills 
653 |a Research methodology 
653 |a Hypotheses 
653 |a Knowledge 
653 |a Project management 
653 |a Vocational education 
653 |a Subject specialists 
653 |a Professionals 
653 |a Interdisciplinary subjects 
653 |a Business analytics 
653 |a Professional Training 
653 |a Competence 
653 |a World Problems 
653 |a Technical Education 
653 |a Science Programs 
653 |a Stakeholders 
653 |a Influence of Technology 
653 |a Scientific Methodology 
653 |a Computers 
653 |a Expertise 
653 |a Educational Technology 
653 |a Talent Development 
653 |a Engineering Technology 
653 |a Apprenticeships 
653 |a Science Experiments 
653 |a Science Curriculum 
653 |a College Science 
653 |a Algorithms 
773 0 |t European Conference on Research Methodology for Business and Management Studies  |g (Jul 2024), p. 136 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3161970820/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3161970820/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3161970820/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch