Computing Science is
the discipline of understanding
computers and the process of
computation, more importantly,
and how to use them what they
can do, what they can't do,
and how to make them work for us
basically.
So, computing science is
very much at the forefront of a
whole range of innovative areas,
both in the pure sense of what
we can do with computers and in
the applied sense in how we can
use those computers to do other
things. It has deep
relationships with mathematics,
so computers themselves and
mathematical objects. And it's a
very scientific discipline as
well. So, what computing
scientists do then day to day
is,
look at computational problems,
figure out how to solve them,
build software to solve it with
maybe even some hardware if you
go down In that little niche
path and apply it, look at what
happens and improve it that
normal scientific process. It's
just now that we're talking
about doing it with computers,
specifically with computers, not
just as a tool, but as the
object of study. And in general,
it's about designing, developing
and implying computational
solutions to computational
problems. So just to give a few
practical examples of that, and
a lot of these you've seen
around you literally every day,
some you may be less familiar
with something like Google Maps.
Like, if you're not already a
computer scientist, you may
think of this oh, this is just
an app on the phone with Google
Maps is a huge computer science
research
topic, essentially in and of
itself, or a combination of
things, because it involves
distributing data to the phone.
so you've got to do control a
network and control data flow to
get information from Google to
the phone and back again. And
that's one of the simpler ones.
You've got to build these maps.
They've got to at least within a
certain degree of error, they've
got to match reality, you've got
to be able to search in these
maps, you've got to be able to
do pathfinding. So if you're
sitting at home and you want to
get to the shops, and you want
to know the route, you've got to
be able to ask Google and it's
got to be able to interpret a
couple of clicks on a map or
taps on a phone and put you on
actual roads. So obviously, you
can just draw a straight line on
the map. But that's not a good
solution. So there's a whole
bunch of computational problems
that are embedded in something
that we now even though it
hasn't been around all that long
that we now completely take for
granted, and use every day. Even
something like Twitter is a big
computational area of interest.
The software itself, I guess, is
relatively straightforward. But
it is this huge example of a
social
network.
It's about how people interact
through a computational medium.
And there are computer
scientists who study things like
this, how to manipulate these
networks, control them, get
information out of them,
understand them. use things like
Twitter as models to apply to
other things that look like
social networks. And again,
there's a whole huge area of
research in social network
analysis, network analysis in
general. And how to understand
these, essentially computational
objects. So it's something like
Twitter doesn't exist outside of
computational perspective,
because you'll all be familiar
with things like facial
recognition. Every iPhone does
this now to some degree, you
hold it up and then unlocks for
you. Getting that to work is a
big computational problem. So
years ago, this is virtually
impossible. But now, this is
getting better and better, every
single day. And this brings
along with this, along with it
ethical considerations as well.
So as a computer scientist, you
have to have to consider
is what I'm doing with this a
good idea.
So not only do you get to build
the software to possibly do
these things, you have to think
about
should I be doing these things
in things that we see don't see
so much every single day there
are things like bioinformatics.
So this is something that is
probably hidden for most people,
but you will have seen a little
bit of it on the news. But
medicine is becoming more and
more computerised. Well, one
part of that area is called
bioinformatics. And there's
other like genome informatics
and related fields like that
proteomics where we have medical
examinations of some kind. So,
say we take a genetic essay of a
whole bunch of patients. those
records are computerised. I
mean, they're inherently
computerised, because all the
machines are computers. Now, of
course, because once again,
we're completely surrounded by
computers. So we have 10s of
thousands to millions of patient
records. And each of those
records contains hundreds of
thousands of genes. So just as
an example, and we want to know
stuff about it, we want to be
able to say, well, this section
of the population has this
disease and this section
doesn't, why did they get it and
why didn't they especially with
things like genetic diseases
like cancer,
Parkinson's and other
diseases that have a significant
genetic component, we can search
through this data as a human. It
is literally billions and
billions of records apart from
as humans having just simple
difficulty in understanding the
raw data, there's too much of
it. So, bioinformatics is the
field of applying computational
techniques to extract
information from the data
to understand it to point us
towards possible future medical
solutions to these problems, to
towards things like us for
cancer or understanding how
particular cancers work so we
can develop better treatments,
understanding how drugs work on
particular diseases, so we can
predict the effectiveness in
particular patients personalised
medicine, all these things
require serious computational
effort
and the solving of
very hard computational problems
as well. So it's not simply a
matter of okay. We have a
database of all these, all this
genetic information, let's find
the answer. There are a huge
number of complicating factors,
and working out what the answer
in and of itself is a hard
problem. So building software to
even start to approach these
problems is difficult to begin
with. So there's a huge amount
of research in this area. We
have other things like social
robotics. So obviously, we all
know what a robot robot is. And
of course, these days robots are
all computerised. Once again,
computers are everywhere. Social
robotics is the relatively newly
emerging area where humans and
robots interact. So we've had
industrial robots for quite some
time. That's a reasonably well
understood field. Obviously,
there's still a lot of work in
industrial robotics. But getting
robots to effectively interact
with humans is again another
very difficult task and it's
something that is right at the
forefront of research at the
moment. And just a nice little
one. That actually combines some
of the background of a few of
these other ones is something
like this shark detection drone.
So this is actually a project
that is, was born at UTS and is
ongoing, and his work with the
use of our lifesaving
lifesaving Association.
If we want to spot sharks to
help protect people swimming in
the water, or even just monitor
things as well, it's very
difficult to post someone on the
beach and give them a set of
binoculars and have them just
watch and hopefully spot that
fin sticking out of the water.
Or it's very expensive to have a
bunch of helicopters floating
above all the beaches, watching
trying to spot the sharks.
If we can train, well, if we can
build an autonomous drone and
train software on it to
automatically recognise sharks,
then we go a long way to making
this process automatic,
effective and
very efficient and cheap because
then we can do it routinely.
And this says,
being done here, UTS. So this
shark detection drone is not
just oh, we just throw a drone
with a camera up and watch it.
It involves complicated
artificial intelligence software
that scans what it sees below it
and tries to identify sharks
and sends that information back
to
whoever's monitoring
it back at base.
So that data can be collected,
analysed and suitable warnings
or actions generated from it. So
you can see from these that,
like it, obviously, I'm hitting
the same point. Again, computers
are everywhere, and they produce
a huge variety of problems, and
not just sort of like, Oh, hey,
the computer's broken, can you
fix it like genuine, social,
economic, logistic, medical,
scientific problems that need to
be solved?
So as you may have guessed from
this,
even though I just had six
little examples, there still
gives you quite a wide range of
things. There's a huge range of
career opportunities springing
from the study of computing
science. So we've got a few
rather direct ones listed here
that these ones are listed,
basically, because they
correspond quite closely to the
majors that we offer. But you
can go into things like being a
data scientists. So building
software, to analyse data in
interesting and new ways. You
can go into the field of
artificial intelligence, where
we effectively try and teach
computers to learn is the sort
of short version of it. It's
actually an absolutely huge
field and covers a wide variety
of different application areas.
But artificial intelligence as
again, as you probably know from
the news is becoming more and
more important because it's
starting to govern a huge swath
of computer systems that we use
every day. And if we get that
wrong, we're in quite serious
trouble. So it's important that
we do this study at sea. And get
it right. This shouldn't be sort
of left to anyone who runs along
and doesn't know anything to
build stuff.
It's a
whole bunch of difficult
problems all mashed into one big
problem. And we need people to
work on that and solve it. You
can also become a software
designer, so not just a
programmer. So programming is
the skill of being able to write
a piece of software. Actually,
designing the software in and of
itself is a difficult task. And
learning how to do that. And
developing new ways of doing
that is, at least for some
people, interesting and
challenging thing to do. Another
new relatively new field that is
becoming more and more
important, again, as computers
take over everything, and
they're embedded in our fridges
and our toasters and other
places that possibly they
shouldn't really be, is a cyber
security analyst. So
understanding the threats
that are posed
to our data to our personal
actual physical beings
by having these computers
everywhere and having them be
secure or not secure is
another
very serious field of study and
understanding how to protect
computers. And hence protect our
data and protect ourselves. So
for example, if a computer is
running our car, and someone
hacks that, that's not good,
sort of not good tm. So being
able to build secure computer
systems is an incredibly
important thing. And something
that's been pretty,
comprehensively overlooked up
until now. So the scarcity of
computers meant that people
could kind of sweep this problem
under a rug, but now that
they're literally everywhere, we
have to deal with this. This is
a really serious problem.
Another emerging field is being
a quantum computing specialist.
So we're just starting to be
able to build actual quantum
computers. So there's a few
essentially prototype quantum
computers that are up and
running, they're not as powerful
as they could be. They're not
ubiquitous yet. But they will
be. And it won't be that long
before they are. And once they
are, we need people who can
actually write software for
them. Because they're not just
another computer with a weird
black box that you can just
throw any old software on. They
require specialised software and
specialised understanding. And
quantum computing is one of the
things that UTS also specialises
in. And on top of all of these,
so these are the ones that I've
just talked about are the sort
of practical industry side of
it. On top of all these, you can
go into the research in any of
these fields and many others. So
where research differs is that
you're not looking at producing
necessarily a direct product
that makes someone money. You're
looking at understanding at a
fundamental level, how and why
these things work, and being
really at the cutting edge of
what The next thing, how is this
going to change? What can we do
that pushes this field further?
That's computing science in
general, and the kind of things
you can do with it. I,
technically you could, in
theory, go to another university
and learn some of those things,
I wouldn't recommend it. So what
we're here, hoping to interest
you in is our Bachelor  of Computing
Science Honours.
So it's an embedded honours
degree. I'll
talk about that a little bit
further in a couple slides. So
it's a degree that has been
designed both in collaboration
with researchers here at UTS
And the well, not just the
software industry, but the tech
industry here in Australia. So
we have a huge variety of
industry partners that UTS
they've had input into how this
degree is designed. We've looked
at what the research parts
available are, and that's been
built into the degree expects
that you have a passion for
mathematics and can be And of
course for programming and
hopefully some other things that
you'll learn as you go along.
And the whole degree is really
focused on in many different
ways on how to solve computation
problems, big problems, hard
problems, intractable problems.
Of course, we don't just throw
you and expect you to do that.
The degree is designed to help
teach you how to do that. So
then by the end of it, you
should be able to develop theory
about a problem that you're a
computational problem that
you're faced with, design a
solution to it, develop the
actual, like software itself,
and apply it in a computational
setting to solve that problem.
And be able to do that for
problems in a range of different
settings. So it's not just, you
know, one little sorting problem
or something like that. What we
give you here is a broad range
of widely applicable skills on
top of some discipline specific
knowledge to be not just a
specialist in a particular
field, but a well rounded
computer scientist. So what you
might be asking is how this
degree differs from the other
ones, because essentially, every
university offers some form of
computer science degree. It may
have a variety of different
names, but it's, you know, it's
a big field everyone's in on.
What we've got here is a few
things that separate the degree
a little bit from the degrees
that are the universities. So we
UTS as a whole has a very
practical Industry Focus
throughout its degrees including
this degree. So we certainly
have a great deal of theory that
goes into this, but we do try to
spend an awful lot of time
getting you to actually do
things
which is not
Actually all that common
throughout, well, any university
degree and particularly Computer
Science degrees around, not just
in Australia around the world,
in your degree, you'll be able
to specialise in at least one
particular area we are. So we
you can choose a mate or you
have to choose a major actual
major actually, you can also
choose a sub major, but another
thing I'll talk about
briefly in a moment.
So this is something that is
missing in an awful lot of
degrees in Australia, there
isn't a coherent path to being
not just a computer scientist,
but a specialist in a certain
area. It's something that UTS
offers that other universities
don't we try and focus on what's
coming up, not just what has
been. So obviously, you have to
learn some things from the past
because everything is built on
top of everything else. But what
we're interested in is looking
at what will happen next. So not
what happened 10 years ago
because like, what's the point
of learning just That. We want
to know what's going to be
useful as you go on in a career
and do new and interesting
things. This degree also has a
very strong research preparation
threat. So this is
something that is very unique to
this degree. You'll see in the
next slide, how this fits in in
terms of subjects. But we have a
series of subjects throughout
the degree. And as I said
before, it's in an honours
embedded degree, we have a
series of subjects that teach
you how to be an effective
researcher, and prepare you for
not just a career in research,
which is sort of the simple
outcome of that, but to be an
independent, effective,
intelligent problem solver,
which is really what research is
about. So some of you may be
coming into the degree going
are, you know, I just want to go
out into industry and go to
Google and then a whole heap of
money. Don't really know how to
need to know how to do research.
But this isn't true. So if you
want to seriously advance in,
even in just the normal software
industry, so even if you don't
want to specialise in some weird
little niche field, having
research skills puts you head
and shoulders above all the
other graduates, because not
only can you reproduce solutions
that you to problems that you've
studied in your subjects, you
can build new solutions to new
problems. And that may not seem
like a lot, but that is a huge
difference. And that's what the
research preparation gives you.
The structure of the degree is
something roughly like this,
it's not absolutely set, but
this is the recommended study
sequence.
So you can see in the first
year,
so obviously, we have two
sessions a year autumn and
spring, first semester and
second semester in most of the
places. So at the beginning,
you'll study for mathematics
subjects, We have a say in the
red day, you can see we have a
series of core subjects in
computing science. And a lot of
these are shared with some of
our other degrees, so you won't
be isolated off by yourself,
you'll be meeting students in
other degrees streams and
talking to them and interacting
with them. So that computing
science core is the component
that gives you essentially the
base or as it says, the core
knowledge of being a computer
scientist. So that is the stuff
where you would go out and get a
graduate position and say, this
means I can kind of do all these
different graduate positions. On
top of that in the blue there,
you can see that we have the
major. So I'll talk about the
majors on the next slide, I
think, or some of the available
majors, and the major is an area
of specialisation.
So on top of being
General, computer scientists
which you get from the core,
you'll also be a specialist in
some particular area. Again,
this is Something that utms has
in its computer science degree,
which is a bit different to a
lot of other computer science
degrees. So something that's
also available now as a sub
major. So you do essentially
half a major, which allows you
to add a little bit of sort of
coherent knowledge about another
topic. So not quite as big as a
major, but you might want to do
say you're interested in
artificial intelligence, but
you're also a little bit
interested in cybersecurity. So
you can do the AI major, and
then do a sub major in
cybersecurity and maybe combine
the two
or maybe not, maybe you do
something completely different.
In the dark grey, almost black
there is selective, so there is
also space in the degree for you
to do things that you're
interested in. I mean, hopefully
you're interested in the rest of
the degree as well. You can add
a bunch of things to that it
might be language study, it
might just be more computer
science subjects because you
really love it. It could be some
of our like software development
studio subjects to get more
hands on practical experience
and things like
that, but there's some fun
ability in there with
being able to choose some things
to customise your degree to
yourself
then in the light and mid grey
there,
so the comp size studio and the
honest project and the honest
project preparation are the
research prep is the research
preparation string for the
degree. Traditionally, the way
an honours degree works in
Australia is that you do three
years of an undergraduate degree
and you get good marks and then
one of the lecturers says, Hey,
you got good marks? Do you want
to come and do honours? And then
you because you're at the end of
the green don't know what to do
you say? Yeah, sure, I'll go and
do honours. What we actually
have in our computer science
degree here is one embedded
honours. So if you're doing
computer science, you will go on
to do honours. But recognising
that honours is a challenging
thing to do. It's well worth it.
Don't get me wrong. This is
having an honest degree is a
very valuable thing. But it is
definitely a challenging thing
to do. We have a research
preparation stream that leads up
into that. So we have two
computing science studios, so one
in your second year, one in your
third year, and they give you
the opportunity to, one learn
research skills, so the first
computing side studio teaches
you the basic things and you're
not expected to suddenly be able
to do new, different research.
The second computing science
studio builds on that, and
allows you to build to develop
those skills a bit more, but
start to push into doing
something new. And then by the
time you get to your honours
project, you no longer have this
big scary thing where it's like,
oh, I've got to do this huge
project. Now. It's actually
Well, I'm just doing the things
that I've been taught to do bit
by bit throughout the degree and
applying it to something that is
probably reasonably new. So you
will actually be doing genuine
research. The other thing that
the computer science studios
allow along with the honest
project preparation is an
opportunity to sample some of
the different research areas
that UTS
obviously there's not quite
enough time to do all of them.
But
if you get lucky, for example,
In your first studio, you'll
find the thing that you love.
And then you can spend both your
studios and all of your honours
working on that. And in
principle, you can make it
almost one coherent project.
So not only do you have this
honours project at the end, but
it's something that you've been
building up to. So by the end,
you're producing something quite
serious. If you get unlucky,
what happens is you find out
that there's an area of research
that you don't like. And then
you go, Oh, that was terrible.
But this is a really important
thing. And never underestimate
the value of occasionally making
bad choices. Because that tells
you that you're not going to do
that for your honours project.
And that is incredibly valued,
valuable because having worked
at a couple of universities,
I've seen plenty of honours
students who've picked an
honours project, basically on a
whim, and they're not finished
because they had such a
miserable time of being able to
go through this sequences, sort
of smaller steps to familiarise
yourself with what's available,
who the researchers are, what
you enjoy what you work well in,
who you work well with, allows
you to have a much more
rewarding and productive on as
experience at the end of the
whole degree. And I can't stress
it enough how much one this is a
thing that is very unique to us
as computing science degree, and
also how useful and valuable
this experiences. So as I
mentioned, you get to choose a
major or have to choose a major,
I should say. And we have quite
a wide range of majors available
in the computing science degree.
So we have a series of majors.
So if you're very mathematically
inclined, we have a series of
majors that are offered
essentially by the mathematics
department in analysis,
operations, research and
statistics.
We also have
a range of majors that link in
both with research and practical
directions available UTS
so we have
two different cybersecurity
majors. So one focuses on the
Sort of software level things
and one focuses on the network
and more of the hardware and not
know exactly hardware, but the
communications end of things. So
depending on what part of
cybersecurity you're interested
in, you might want to do the
cybersecurity privacy, or the
networking cybersecurity major.
We have a
quite wide ranging data
analytics and artificial
intelligence major. And so it
covers a whole bunch of those
data analytics and artificial
intelligence things I've been
talking about before, including
things like Bioinformatics,
which I
rambled on about a bit at the
start.
We have
enterprise systems development
major, which is our sort of
core, I want to be a software
development developer, I want to
go and work at Google kind of
major.
Not that the others aren't that
either.
But it's all about how to build
effective software systems.
We also have a Business
Information Systems Management
major,
so it's more about the
system level of software
development rather than the
software level of software
development. So, a lot of these,
you still share
a number of subjects
as well. So, of course, you've
got your core subjects, so
everyone learns to programme.
Everyone wants to do at least
some of each of these. But these
give you a specialisation. So
Business Information Systems
then says, Well, how do you
think about these things as a
system that interacts with
humans, as distinct from
enterprise systems development,
which is how do I build these
things in the first place, we
also have an interaction design
major. So if you're really
interested in how humans
interact with computers
directly, and how that can be
made more effective, more
accessible, more usable,
interaction design is something
that you might be interested in.
And brand new studying this
year, is the quantum information
science major. So if you're
really interested in quantum
computing, and the real cutting
edge of that, that's the major
view. That's a whole bunch of
have information about the
degree and probably most
scarily, I've mentioned
mathematics a few times already.
And one of the big questions we
always get is, oh,
how much mass do I need to do?
How much am I expected to know?
So,
UTS as a whole, including
computing science degree does
not have any prerequisite
prerequisites whatsoever, apart
from the entry mark.
Obviously, if you've done
mathematics,
and did mathematics, extension,
one or two, that's great. You'll
have a surer footing when you
come in. If you've done advanced
English, that's also great,
because the other scary thing is
we expect you to be able to
communicate. I know that's not a
popular thing amongst computer
scientists, me being one of
them, I perfectly well
understand that, but is a thing
that you have to do. So there
are a couple of things where if
you've done them, that's great.
If you've done software design
development, also, that's great.
You'll be on a, again a shorter
footing, but we don't expect any
of that. And we certainly don't
assume that you've done any of
those things. So all we assume
that you when you come in is
that you've done the HSC, or
some sort of equivalent. So
there are definitely alternative
pathways into degree as well.
And that you have some basic
mathematical understanding. But
once you start the subjects
here, they all start from the
beginning. So they don't assume
that you know anything about the
thing that they're teaching.
They start from the beginning
and
you're even with everyone else.
So don't panic if you haven't
done that extension one. That
doesn't rule you out that
doesn't certainly doesn't really
hurt from the degree. Although
computers are very mathematical
object.
A good chunk of the students are
not
super keen on mass love
programming. So they, so really,
they are actually keen on mass.
They just don't know it yet. So
one thing I mentioned just then
was that essentially the only
prerequisite we have is the
entry mark. So the entry mark at
UTS is a combination if you're
coming from high school is a
combination Have your ATAR
and adjustment points.
So there's a number of ways that
you can achieve adjustment
points, the total number is
capped at 13. All degrees have
a secondary
cutoff that you have to get a
rate of at least 69. So if you
get lower than that, then you
have to look at alternative
ways. But once you're over that,
you can also get a series of
adjustment points, which help us
really work out
whether you're suited to this
particular degree or not.
So there's a
URL just below here uts.edu.au slash
future students slash
undergraduate slash admission
desk requirements slash
admission schemes, which has a
full listing of all these
adjustment points, how you can
apply for special circumstances
ones how to fill out the UTS
engineering it questionnaire and
so on. If you missed that you
URL, just go to the front page,
go to future students and follow
the links and you'll get there
it's actually pretty easy To
find one of the other really
important things that you Ts is
that we have a very high level
of student support. So
again, going back to the scary
mathematics,
part of the degree,
if you're really unsure of your
mathematics ability and a little
nervous about coming in, UTS
offers bridging courses in
mathematics specifically. So
that's the most directly useful
for this degree. So there are
things you can start doing
before you even start your
normal subjects that we can help
you to prepare for those normal
subjects.
And one of the other things that
I want to mention here,
obviously, because it's on the
slide, is you pass so for some
of the subjects so those that
students find particularly hard,
we have a peer assisted study
scheme. So this is something
that runs in parallel to the
subject is not overseen by the
subject coordinators but is
overseen by an administrative
team and students who have done
the subject unwell and have done
well, and there are other
subjects.
And what it offers is a way to
talk to other students about
what's happening, get their help
in doing the subjects. So you're
not alone in doing these things
where you can go and talk to
other students who
do know the answers, because
I've already done it.
So I can help you in a much more
relaxed environment in a normal
classroom. And you can get
something that's a bit more
tailored to you as well. On top
of that, we have a whole bunch
of other student support schemes
as well. But you'll get to see
all of those when you come in
for their
orientation sessions at the
start of uni.
So hopefully, you found
all that interesting and
inspiring. And if you want to
get a bit more engaged, we have
a few ways that you can talk to
us. So we have obviously a
Facebook page UTSFEIT
Instagram page,
or account, I should say,
you if you want to email any
questions that have been
prompted from This or any other
discussions or anything that
you've seen emails that fit at
UTS.edu.au If it's an
enrollment thing that will be
directed to people know about
enrollment, if it's a specific
subject thing that can be
directed to an academic, you
might be able to answer your
questions quite directly. So
it's sort of a collection point
to then send it out to someone
who knows what it is.
And if you just want to come and
visit us on the web,
it.uts.edu.au
