Master of Data Science

class="m-0 section-title__container anchorname" id="admissions"> Entry requirements and admissions You need to satisfy all of the following entry requirements to be considered for entry into this degree. Expand all sections Collapse all sections Academic requirements Prerequisites Selection tasks English language requirements Academic requirements You must have: An Australian bachelor degree in computing, science, engineering, or health, or statistics with a GPA of at least 2.0 out of 4.0, or equivalent. OR You may also be considered if you have an Australian bachelor degree with a GPA of at least 2.0 out of 4.0, or equivalent and; relevant completed courses in programming and statistics in an undergraduate or postgraduate degree or a minimum three years’ of current, relevant work experience or professional practice as a programmer, statistician or equivalent. If you wish to have industry or employment experience assessed as part of meeting the entry requirements you will need to provide a detailed CV/resume listing previous positions, dates of employment and position responsibilities; a statement from your employer confirming these details (or contact details of employer so RMIT can seek confirmation); and evidence of any relevant professional development undertaken. International qualifications are assessed for comparability to Australian qualifications according to the Australian Qualifications Framework (AQF). Prerequisites There are no prerequisite subjects required for entry into this qualification. Selection tasks A selection task is not required for entry into this qualification. English language requirements You must meet the University's minimum English language requirements to be eligible for a place in this course. You need to satisfy all of the following requirements to be considered for entry into this course. Expand all sections Collapse all sections Academic requirements Prerequisites Selection tasks English language requirements Academic requirements You must have: An Australian bachelor degree in computing, science, engineering, health, or statistics with a GPA of at least 2.0 out of 4.0, or equivalent. OR You may also be considered if you have an Australian bachelor degree with a GPA of at least 2.0 out of 4.0, or equivalent and; relevant completed courses in programming and statistics in an undergraduate or postgraduate degree or a minimum three years’ of current, relevant work experience or professional practice as a programmer, statistician or equivalent. International qualifications are assessed for comparability to Australian qualifications according to the Australian Qualifications Framework (AQF). Prerequisites There are no prerequisite subjects required for entry into this qualification. Selection tasks A selection task is not required for entry into this qualification. English language requirements To study this course you will need to complete one of the following English proficiency tests: IELTS (Academic): minimum overall band of 6.5 (with no individual band below 6.0) TOEFL (Internet Based Test - IBT) for Australia: minimum overall score of 79 (with minimum of 13 in Reading, 12 in Listening, 18 in Speaking and 21 in Writing) Pearson Test of English (Academic) (PTE (A)): minimum score of 58 (with no communication band less than 50) Cambridge English: Advanced (CAE): minimum of 176 with no less than 169 in any component. Note: RMIT does not accept scores from 'at-home' or 'online' testing. For detailed information on English language requirements and other proficiency tests recognised by RMIT, visit English language requirements and equivalency information . Don't meet the English language test scores? Complete an English Language Pathways (Academic English) Advanced at RMIT University Pathways (RMIT UP). Additional information Expand all sections Inherent requirements Non-academic abilities you'll need to complete this course The following information outlines the tasks you will be required to undertake during professional experience placement and on-campus learning activities. The non-academic abilities listed are provided for your information only and are not entry requirements. By understanding the types of activities you'll participate in, you can: understand more about the course determine if you may need support during your studies make an informed decision about whether the course is suitable for you. Adjustments If there are any activities outlined which may be difficult for you to undertake, there is a range of adjustments to your study conditions available to enable and support you to demonstrate these abilities. Please contact the Equitable Learning Services (ELS) team to discuss any adjustments you may require. To receive learning adjustments, you need to register with ELS. If you are living with disability, long-term illness and/or a mental health condition, we can support you by making adjustments to activities in your course so that you can participate fully in your studies. The University considers the wellbeing and safety of all students, staff and the community to be a priority in academic and professional experience placement settings. View inherent requirements <div

class="m-0 section-title__container anchorname" id="career"> Career Any organisation handling large volumes of data needs qualified data scientists. Across all sectors of the economy – including IT, business, banking and finance, science and engineering, government, health and medical – organisations can gain a competitive edge by better managing and analysing their data. As data science is still a new and emerging field, the roles available are quite varied and diverse. As well as the title of data scientist, other positions include analytics specialist, business intelligence analyst/developer, data analyst, data architect, data engineer, data miner, research scientist and web analyst. While industry expertise is at the heart of this degree, studying at RMIT also means you are physically located close to Melbourne’s data professionals in the central business district – with many opportunities to forge links with local industry and jobs, including meet-ups, events and seminars, as well as other networking occasions. After being exposed to the latest theoretical and practical expertise, graduates are expected to become influential leaders within their organisations. There is also a research stream in this course, in which students work with a data science researcher on more technical data science innovation. Expand all sections Professional recognition and accreditation The Master of Data Science is fully accredited at a Professional level by the Australian Computer Society (ACS) for students who commenced study during the period specified on the ACS website. ACS is a signatory to the Seoul Accord, which means graduates are internationally recognised. See ACS for more information on the Accord provisions and ACS membership. Students and graduates can join the Institute of Analytics Professionals of Australia (IAPA). IAPA is the professional organisation for the analytics industry in Australia, incorporating business analytics and data mining across multiple disciplines and sectors. <div