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 os
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, and 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.
