The ability to make sense of data is crucial for any business hoping to succeed in today’s digital environment.
So who provides the expertise and builds the infrastructure to harness ever-increasing volumes of information?
The Master of Data Science at RMIT offers in-depth statistics and computer science knowledge to equip students with sought-after skills to manage and make sense of digital information.
Associate Professor James Thom has led the development of this new program. RMIT spoke to him to find out more about this burgeoning area of science, strongly touted as an “area to watch”.
What is Data Science and why is it so important?
We live in a data-driven world that’s generating a great variety of data at ever increasing rates – social media, financial transactions, telecommunications, even scientific discovery – so it’s no surprise that the role of data scientist has been labelled by the Harvard Business Review as the “sexiest job of the 21st century”.
Consequently, handling all this data is a top priority for all of us, whether you’re talking business, government and other organisations, or even individually as citizens and consumers.
Managing and making sense of this information is the emerging interdisciplinary field of Data Science, which combines areas of computer science with mathematical statistics and domain expertise.
Who needs qualified graduates in Data Science?
Any organisation handling large volumes of data needs qualified data scientists. Organisations in all sectors of the economy – IT, business, science and engineering, government, medical – can gain a competitive edge by better managing and analysing their data.
Who is suited to the field and what can students expect from the master program at RMIT?
Becoming a data scientist could appeal to people interested in analysing big data from a whole range of different backgrounds, and for RMIT’s Master of Data Science program we are seeking graduates with a computing, mathematics, science, engineering or health background.
RMIT offers master programs in both Data Science and Analytics. Although both masters share a number of courses, the Master of Data Science contains a significant core of both computer science and statistics. This prepares graduates for a career working in a field that is driving scientific research, economic growth, public policy and corporate strategy, using cloud technologies to aid the management and analysis of very big datasets.
The program is taught by academics with strong research backgrounds and links to industry, as well as sessional teachers and guest lecturers currently working in industry.
After receiving exposure to the latest theoretical and practical expertise, graduates of the Master of Data Science are expected to become influential leaders within their organisations.
What and how will students learn?
The first year of the program develops a solid foundation in computer science and statistics – core skills necessary for every data scientist in their professional work.
Students with an undergraduate background in either of these areas may gain some advanced standing, whereas students from other disciplines will first complete the introductory courses needed to prepare them for studying the advanced core courses and electives in the second year.
The second year also includes a major project, which can be working on an industry or research project while based on campus, or off campus as an internship working as a data scientist in industry.
The real-world focus of this program provides an excellent networking environment that can lead to internship and industry-led project opportunities.
Data scientists are often dealing with highly sensitive personal data, so it is imperative that before working on industry projects (for example, as an intern) students undertake case studies with input from industry-based data scientists looking at the legal, ethical and policy issues in data science.
Are there any unique facilities or equipment students can benefit from?
Academics who teach in the master program are also involved with RMIT Data Analytics Lab, which is a hub for advanced data analytics projects, supporting researchers and helping Australian and Victorian businesses compete on a global scale.
Originally launched as a joint initiative between RMIT University and National ICT Australia (NICTA) – now Data61 – the lab applies text, user and data analytics research to industry-driven projects that solve problems and provide efficiencies in key areas including health, logistics, smart cities, environment and security.
With its industry links and data focus, the lab is an excellent resource for master students to gain networking access to researchers in the field and project partners.
What are the burgeoning areas in this field, i.e. where are the jobs?
Job titles for data scientists in this new field are very diverse. In addition to the role of data scientist, these include: analytics specialist, business intelligence analyst/developer, data analyst, data architect, data engineer, data miner, research scientist and web analyst.
Many of these jobs are in the Melbourne central business district and the adjacent biomedical and knowledge precinct to the north, right next to RMIT.
While industry expertise is at the heart of program delivery, studying at RMIT also means you are physically located close to both these areas, providing many opportunities for developing links to local industry and jobs.
For example, local ‘meet-ups’ provide clear pathways into the data science community on both a social and professional level. Those of us involved in teaching the program, whether from industry or academia, attend these meet-ups ourselves and we expect that our students will join those that follow their interests too.
As an expert in this area, what inspires you the most about Data Science and where to you see this area in five years?
I have led the development of the Master of Data Science at RMIT, because I am passionate about how computers can efficiently and effectively handle the volume of data that is created everywhere; both in our human daily lives as it underpins the new digital economy and as a new fourth paradigm of scientific research.
Although I am not sure that I would describe data science as the sexiest career of the 21st century, it is undoubtedly one of the most important specialisations for handling our data-drenched present, as well as being a vital factor in ensuring our economic, scientific and ecological future.
As for its future, world-renowned Big Data Scientist, Vitaly Gordon said in a recent article that we’re not even realising how big data science will become, so we’ll have to wait and see.
Story: Sarah Morley