It's time for another data science in Australia Q&A. It's been a whole year since I did the last
one, so we were long overdue. Today I'm gonna answer your hardest questions that I've gathered
from the comments section as well as Instagram. So if you missed submitting any questions this time,
be sure to follow me on my Instagram for the next Q&A. I'm Samanvay, a data scientist living in
Sydney, Australia. So the first question is, what made you want to get into data science or why data
science? I initially did an aerospace engineering degree and put it into data science as my first
graduate role, so there were really three key reasons why I switched into data science. The
first was that in data science, as it was mainly software-based, you could create and build data
products very, very quickly that would have a large amount of impact. Now this was very
different to Aerospace which is a very cyclic industry which has an extremely long feedback
loop, and that basically means that because you're dealing with Hardware, you can't just create
something extremely quickly, break it and improve upon it in a very short amount of time and not
to mention that there aren't many jobs like that where you actually get to create new things from
scratch on a daily basis. Now the second reason was the ability to have an impact into multiple
Industries because data science is used in almost every industry. You can imagine you get to work
on a variety of problems. The third was really to learn software skills that I could one day use to
create my own startup because coding is something I always enjoyed throughout my University career.
So it wasn't completely out of the blue that I wanted to go into software, and of course,
if you want to know more about my transition from aerospace engineering to data science,
then be sure to check out my Aerospace to data science video. So the next question is,
what is your favourite thing about data science? Now for me, this has to be the range of ambiguous
problems you have to solve because you are dealing with data; there is an infinite number of problems
you could really solve with it in any given industry, which really means that you're never
bought on the job. Now across my six years as a data scientist, I've worked across a variety of
data sets from Finance to Aerial imagery to retail. The number of Industries you can do
data science is ultimately Limitless, and that, to me, is extremely exciting. Next question is a
twofold question so what is the scope of data science in Australia, and what is the type of
degree you should do for your Masters to get into it? The scope of data science in Australia
is huge. After the end of covid, Australia has opened The Floodgate to International students
and skilled migrant workers. The quotes for PR have drastically increased by over
35,000 this year alone. Tech industry in Australia is heavily reliant on migrant workers, so there's
definitely enough data science opportunities to go around. As for what is the best master's degree to
do data science in Australia, it would definitely have to be a master of data science or a master
of computer science. Now if you're definitely more coding and software inclined, I would suggest you
to do the master of computer science because that keeps your doors open to other forms of software
engineering, such as front-end development or back-end development in addition to data
science so you always want to preserve the amount of optionality you have early on in your career.
The next question is closely related, which is, does your course have to be ACS accredited for you
to get a job after? So ACS stands for Australian Computer Society, and a lot of software courses in
Australia tend to be accredited by ACS. It's often the case that a lot of the master of data science
or Bachelors of data science degrees are not yet accredited by ACS and it doesn't really matter
because most employees aren't really looking at the ACS accreditation when they look at
your CV. At the end of the day, they only care about your education and your competencies as
well as your work experience, and those are the things that really matter rather than a degree
is accredited by some organization like ACS. The next question is, what are the job prospects for
graduates after doing a master of data science? In summary, getting a job as an international student
in Australia is difficult. There's definitely no two ways about it, but it's not impossible,
and a lot of times, it relies on your ability to successfully network to get your foot in the door
and I've previously made a video exactly about this topic showing you the different avenues to
practice your networking skills to get internships as well as a job later on. And to add to this,
I know quite a few graduates of Master of data science that have eventually found jobs,
and the thing common between all of those is their previous work experience, their internships during
their degree and their interest in doing networking events and if you're interested
in a personalized approach to learning networking then feel free to sign up for one of my coaching
sessions where I like to personalize a lot of the advice I give to you so it is the most impactful
for your individual situation. How do you choose a university to study data science art in 2023. So
a lot of the advice here is no different to what I covered in my Master of data science video as
well as the Bachelor of data science video, so I'll leave the links in the description below so
that you can go ahead and look at those and I'll also share the notion table that I built with
the catalogue of all the available data science degrees in Australia and also let me know in the
comments whether or not you want me to do another take of the best universities to do data science
in 2023. So the next questions are all the related to immigration around PR Pathways as well as what
to do given that the data scientist profession is not in the skilled occupations list. So let me
address that one first which is the data science profession not being listed on the migration
list. So one of the requirements to go down the PR pathway is being on the skilled occupations list,
so data scientists, while it's not explicitly on there, there are two professions on there such
as the analyst programmer and the ICT business analyst where a lot of the responsibilities in
those two roles overlap greatly with that of a data scientist. Well, one requirement of the PR
application is that your job can be closely related to some of these other professions.
So once you start your PR application process, you would go to accredit your skills by the Australian
Computer Society, which will determine how close your degree and skills are to these skilled
occupations list professions and I've linked a blog post below which will go through the
PR pathway process in a little bit more details. What are your thoughts on the impact of ChatGPT in
school? in my opinion, students should be allowed to use it. It's just that the education system is
going to change very rapidly to accommodate for ChatGPT. Schools are going to need to move from
a content-based education system to that which fosters creative and critical thinking teachers
will not have to teach students how to critically think when it comes to dealing with responses from
ChatGPT, and one of the most exciting things about ChatGPT in the learning environment in
a school environment is the expected increase in personalized learning. Now teachers will be able
to curate personalized learning plans for each of their students, and not to mention that ChatGPT
will also alleviate a lot of the admin tasks that is currently done by teachers. Now for one of the
hardest questions which is, will ChatGPT take over the jobs of data scientists or data analysts? so
if you follow my channel, you'll notice that my last video was exactly on this topic, and
as I mentioned in the video, there'll be less of a need for data scientists to be working on models
day in and day out, given that GPT is ushering in a new wave of AI as a service product so data
scientists, for example, will be more responsible for trying to figure out exactly what mathematical
or statistical or algorithmic approach to take when it comes to solving a data problem and as for
data analysts they'll still be doing a lot of the rudimentary work of extracting insights from data
but obviously they can leverage ChatGPT to their advantage to be able to get to these insights
quicker but they still will be responsible for creating the context around which these insights
are to be used and making business suggestions off the back of this. So the role of a data analyst
will move beyond that of someone that analyzes their not to also someone that suggests a lot
of business operational improvements off the back of those insights. Next question is, do you use
ChatGPT on a day-to-day basis in a work context? whenever I'm writing code I prefer to go to Google
rather than ask ChatGPT because more often than not I'm trying to search for answers for very
peculiar code problems and often if I ask ChatGPT for something like this I end up cleaning up that
code or rewriting it all over again and if you're using ChatGPT for a lot of these programming use
cases for work I would highly encourage you to be very careful and you really never know when you
might go from asking ChatGPT about code related questions to feeding it proprietary information
because it can be very easy to accidentally make that mistake now the final question is probably
the hottest one for this Q&A which is, what is the expected average graduate salary for a day
data scientists after doing their master's degree? I would say it's around 105k including super so in
Australia we usually have two components to the salary one is the base component and then there's
the super component and the super is usually ten and a half per cent on top of your base
salary. Some companies also have bonuses or equity structures that are added to the base plus super
components so 105k is definitely a lot higher as a starting salary than before COVID times
and the reason for this increase is definitely how hot the market is in addition to the cost of
living increases and inflation increases over the last couple of months so that's all for this Q&A
session. If you enjoyed the video then smash that like button and I'll see you next time!