Speaker: What’s unique about the course, first and foremost, is that students engage with data science and innovation. So looking at those two things together is something that makes us a pretty special program. We were the first in Australia to tackle both those aspects and put them together.
New speaker: The teaching style of this course is a little bit different from a conventional university course. We do have lectures, obviously. But there’s a lot of project work, there’s a lot of group work. And there’s a lot of practical work through our interactions and our connections with industry.
New speaker: The way we are learning is very open and dynamic. You get the theory, but you have to put in practice almost straightaway. So it’s really focused on how you apply your learning and make sure you learn it right.
New speaker: What I’ve really enjoyed about the MDSI is that they’ve expanded on what we can do to get assessed for our knowledge. One example of that is that they’ve really encouraged us to participate in hackathons, which is a great chance for students to demonstrate real-world skills in the data science space outside of a traditional university framework, and learn a whole lot in the process.
New speaker: The kinds of hackathons we focus on in MDSI are data hackathons. So that’s where organisations come in with some burning questions that they have. That they may have been trying to solve themselves, and they put it out as an open challenge.
New speaker: We have a deep engagement with industry. Our connections to partners from industry help us to shape our curriculum. We also look to those connections to help us to deliver the curriculum. In addition to that, we’ve been crafting a number of opportunities as internships. So that our students have an opportunity to actually sit within an organisation. And experience data science practice in a real-life, day-to-day context.
New speaker: Data science is a capability that’s growing to become a part of every industry. Everybody can take advantage of data science. I’ve spent the last six months mentoring one of the master’s students in their first project unit. Together we’ve been exploring how to analyse social media data in real-time. To make better customer decisions about how we can support and provide great customer service to those in a much quicker way.
New speaker: Already I utilise what I’m learning in my day-to-day job. So I sit in the data science team where I’m employed and I can really see the application and the output. So that’s really beneficial, but I also think that it’s all of the skills that I’m learning enable me to shape my career with exciting opportunities.
New speaker: Data science and big data are so important. Because it allows us to take real-world data and turn it into something that can inform decision making. And informing decision making that will actually change and help people’s lives. Improve people’s lives.
New speaker: I think an important aspect of data science that people don’t realise is that there is a creative element to it. Data doesn’t speak for itself. You have to bring your own perspective to it, and you can shape the story that you tell. And that story, how it’s shaped, doesn’t reside in the data itself. It resides in how you think about the data. Your background, your ethics, your values. And these are kinds of things that are becoming ever more important in the present-day world.