国际学生入学条件
A minimum of a level 8 (honours degree) qualification(2.2 or higher) on the National Qualifications Framework. Applicants may be from a cognate/STEM background and standard applicants for the programme are those holders of computing or numerate degrees.
For candidates who do not have a level 8 qualification, the college operates a Recognition of Prior Experiential Learning (RPEL) scheme - meaning applicants who do not meet the normal academic entry requirements, may be considered based on relevant work or other experience. Non-English speaking applicants must demonstrate fluency in the English language as demonstrated by an IELTS academic score of at least 6.5 or equivalent.
TOEFL IBT - 86
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雅思考试总分
6.5
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雅思考试指南
- 雅思总分:6.5
- 托福网考总分:86
- 托福笔试总分:160
- 其他语言考试:PTE Academic: 58
CRICOS代码:
申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
该计算机课程旨在产生高质量
This computing course aims to produce high-quality, technically competent, innovative graduates that will become leading practitioners in the field of data analytics.<br><br>Upon completion of this course, graduates will be able to:<br><br>Conduct independent research and analysis in the field of data analytics.<br>Formulate and implement a novel research idea using the latest industry practices.<br>Demonstrate expert knowledge of data analysis, statistics, and the tools, techniques and technologies of data analytics utilised in both technical and business contexts.<br>Critically assess and evaluate business and technical strategies for data analytics.<br>Develop and implement effective business and technical solutions for data analytics.<br>Critically appreciate ethical and data governance issues relevant to data analytics<br><br>The course structure accommodates a wide audience of learners whose specific interests in data analytics may be either technically focused or business focused.<br><br>All students will also gain exposure to pertinent legal issues and product commercialisation considerations associated with the data analytics field. The course will be delivered using academic research, industry-defined practical problems, and case studies. This approach will naturally foster a deeper knowledge of the subject area and create transferable skills for work such as critical thinking, problem-solving, creative thinking, communication, teamwork, and research skills. The course is completely delivered by faculty and industry practitioners with proven expertise in data analytics.<br><br>Duration - 1 year
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