国际学生入学条件
Applicants to the Master of Data Science will normally have:
a Bachelor degree or equivalent from a recognised higher education institution with a minimum of one year of full-time study in Mathematics or Information Technology or Data Science or a combination thereof, OR
a Graduate Certificate or Graduate Diploma in Data Science or equivalent from a recognised higher education institution..
IELTS total [6.5] IELTS reading [6.0] IELTS writing [6.0].TOEFL PBT- 577 with TWE of 4.5. TOEFL IBT - 79 with Reading and Writing not less than 18.
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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:79
- 托福笔试总分:577
- 其他语言考试:PTE - 58 with Reading and Writing communicative scores not less than 50.
CRICOS代码: 079912G
申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
UniSA的数据科学硕士为您提供有关数据科学技术和研究的最新知识。它针对具有数学或IT背景的学生,并针对这两种课程量身定制。您将学习分析和可视化丰富的数据源,如何发现数据趋势以及如何生成数据管理策略。该课程是与包括澳大利亚分析专家协会在内的行业和业务分析软件SAS的领导者一起设计的。学生还将受益于UniSA在8800万数据到决策合作研究中心中的领导作用。在主要研究人员的指导下,您将学习如何分析和可视化丰富的数据源,如何发现数据趋势并生成数据管理策略。该研究生学位是作为三个课程(研究生证书,研究生文凭和硕士
UniSA's Master of Data Science gives you current knowledge of data science techniques and research. It caters for students with a mathematics or an IT background, with courses tailored for both.You will learn to analyse and visualise rich data sources, how to spot data trends, and to generate data management strategies. The coursework has been designed with industry including the Institute of Analytics Professionals of Australia and the leader in business analytics software – SAS. Students also benefit from UniSA's lead role in the 88 million Data to Decisions Cooperative Research Centre.Taught by leading researchers you will learn to analyse and visualise rich data sources, how to spot data trends and to generate data management strategies.This postgraduate degree is offered as part of a suite of three programs (graduate certificate, graduate diploma and master). Each qualification extends to the next, so you can easily transition to a master level qualification.You will start by developing foundation skills in data and statistics such as big data basics, statistical programming for data science, and relational databases and warehouses.<br><br>Career outcomes - : The field of data science field is evolving at a rapid rate. It will continue to grow as savvy business leaders integrate analytics into every facet of their organisation. Analytics, science, data, and reasoning are becoming embedded into decision-making processes, every day and everywhere in the business world1.<br><br>Careers to consider:<br><br> big data visualiser: using visualisation software to analyse data, drawing implications and communicating findings, providing input on database requirements for reporting/analytics, acquiring, managing and documenting data (e.g. geospatial), creating visualisations from data or GIS data analysis<br> data scientist: understanding interfaces, data migrations, big data and databases, taking the lead in processing raw data and determining the best types of analysis, mining large volumes of data to understand user behaviours and interactions, communicating data findings to IT leadership and business leaders to promote innovation<br> business data analyst: working with stakeholders, analysts and senior management to understand business strategy and the questions that need to be asked, identifying research needs, designing experiments and making recommendations based on results, driving complex analytics projects to support the business<br> information security analyst: reporting and recommendations to prevent security incidents, security control monitoring, implementing new security technology, methods and techniques, championing security best practice, reviewing systems for security risks and compliance issues
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