学历文凭
Bachelor Degree with Honours
专业院系
信息系统
开学时间
课程时长
课程学费
国际学生入学条件
A Level 8 primary undergraduate honours degree with a minimum Pass classification from a recognised third level institution in a non-cognate area and ideally be able to demonstrate mathematical problem solving skills as part of previous programme learning. i.e. maths at Leaving Cert level would suffice.
A minimum Level 7 Ordinary Bachelor's degree in a cognate area such as computer science,technology, networking, information systems, engineering, general science, mathematics, statistics, data science.
IELTS score 6.00
Applicants who do not have a Level 8 qualification and who have at least 3 years work experience may also be considered through the college's normal RPL procedures. Relevant professional experience may be taken into account and individuals will be assessed on a case - by-case basis through DBS RPL procedures.
IELTS - 6
IDP—雅思考试联合主办方
雅思考试总分
6.0
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- 雅思总分:6
- 托福网考总分:60
- 托福笔试总分:160
- 其他语言考试:Duolingo English Test 105 (or equivalent)
课程简介
The Higher Diploma in Science in Data Analytics provides the practical knowledge and skills in the area of computing and data science for learners who wish to upskill or reskill in this area. The programme aims to develop learners' knowledge of the theory and practice of Data Analytics necessary for them to secure employment and perform as graduate level ICT /Data Analytical practitioners in a broad range of commercial, industrial and public sector environments. Learners will benefit from theoretical knowledge fundamental to apply advanced analytics in web and business application, predictive modelling, statistics, programming, machine learning, and advanced visualisation to data sets through a variety of tools and techniques in order to generate actionable insights for stakeholders and support strategic decision making.<br> The objectives of the programme are to:<br>Develop learner's criticality in order to analyse industry trends in Big Data.<br>Develop learners who are capable of performing robust, significant reports on the future orientation of the field of data analytics with specific emphasis on the problem domain.<br>Provide learners with a platform to develop the requisite technical and design skills required by industry and to deepen knowledge of statistical analysis and analytical models.<br>Enable learners to implement scalable Big Data applications.<br>Prepare learners to work effectively and collaboratively in the execution of common goals.<br>Provide work opportunities where learners can apply knowledge to a real-world situation.
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