Data Science Strategy & Leadership (Master Degree)

RMIT Online Australia

Cricos: 00122A

For more information about Data Science Strategy & Leadership at RMIT Online, please visit the webpage using the button above.

The award
Master Degree

How long you will study
find out

Domestic course fees
find out

How you will study
online

Course starts
January, March, May, July, September, October

International course fees
AUD 3480 per module

All study options

About Data Science Strategy & Leadership at RMIT Online

Get ready for the future of data science

The RMIT Online Master of Data Science is for those wanting to be future C-suite leaders of organisations that are, or need to be, shaped by data science and transformed for the future.

Big data is driving the demand for a new type of business leader who can be the critical link between technology and organisational strategy. According to Burning Glass Technologies jobs that combine both technical and transferrable skills are growing at twice the rate of the overall job market, they are 20-40% higher-paying than their more-traditional counterparts, and they are now entering every domain of business.

That's why RMIT has collaborated with industry to design the Online Master of Data Science.

In this program, you can gain the advanced strategic, leadership, data science and analytics (DSA) capabilities required to influence executive leadership teams and deliver organisation-wide solutions driven from data science, machine learning, and Artificial Intelligence. You will learn in-demand data science skills that can be applied across key business functions.

Develop strategy and leadership skills to engage, communicate and influence at an executive level. Understand the language and capabilities of emerging opportunities in AI and machine learning to solve business problems. Learn ethical models for managing, governing and implementing data-led initiatives.

Nested Qualifications

Our Master of Data Science Strategy and Leadership encompasses courses that make up a Graduate Certificate in Data Science and Graduate Diploma in Data Science Strategy and Leadership (exit point only), so, should you need to exit the program early, you can still earn a postgraduate qualification by successfully completing specified courses.

Advanced Standing

Those with minimum two years proven experience in data science and relevant honours or masters level degree in a cognate discipline may be eligible for advanced standing for up to four courses in the Graduate Certificate of Data Science. This means students can complete the masters by studying just eight courses. A Student Enrolment Advisor can tell you more about advanced standing eligibility on 1300 701 171.

Study options for this course

  • The award How you will study How long you will study Course starts Domestic course fees International course fees
  • The awardMaster DegreeHow you will studyOnlineHow long you will study find out
    Course startsJanuary, March, May, July, September, OctoberDomestic course fees find outInternational course feesAUD 3480 per module

Entry requirements

An Australian Bachelor degree (AQF 7) or equivalent from a recognised tertiary institution in Business; or

An Australian Bachelor degree or equivalent in any non-business discipline with a minimum of 3 years Full-Time Equivalent (FTE) work experience in an industry setting. Applicants will be required to submit a CV; or

Successful completion of the RMIT Graduate Certificate in Data Science AND with a minimum of 3 years Full-Time Equivalent (FTE) work experience in an industry setting. Applicants will be required to submit a CV; or

Australian Graduate Certificate, Graduate Diploma or Master's degree or equivalent in Business (or a related discipline).

International students are required to provide current evidence of English language proficiency for admission to RMIT University. For detailed information on English language requirements and other proficiency tests recognised by RMIT visit the English language requirements and equivalency information.

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