Doing a master of data science degree is not always useful to getting a data science
job. Today I'll talk about who should or should not do this master of data science degree. For
some of you out there doing a master of data science degree is a terrible idea but for others
it means the start of a data science career. I'm Samanvay, a data scientist living in Sydney,
Australia. Doing a master of data science degree takes a lot of time and a lot of money. The
average data science degree will take you around two years to finish and it means spending anywhere
from $40,000 to $70,000 on the entire degree. Spending this much amount of money on a degree is
not a joke. Given these huge commitments, it makes sense to figure out which is the right option for
you and whether or not you decide to do a master of data science degree depends on your educational
background. I'm based in Australia, so I'll talk in the context of doing the degree in Australia.
So typically there's two types of people that want to do a master of data science degree. The
first is recent bachelor students and the second is the mid-career transitioners. Let's first talk
about the bachelor's student. There's three types of bachelor students that would consider doing
a master of data science degree. The first is a bachelor student from Australia with a stem
degree. For you I would recommend not doing the master of data science degree. You're much
better off leveraging your technical skills to score job as a data analyst or junior engineer
because this means that you're being paid to learn on the job and in your spare time you can
self-study data science and I've got tons of resources on my youtube channel as to how to study
data science on your own. So once you're racked up a couple of years of experience you can then
switch to a data scientist position or machine learning engineering position. Typically in
Australia your practical on-the-job experience is more valuable than your degree. Now as for
the second type of bachelor's student will be a bachelor of students from Australia in a non-stem
field. For those people I'd recommend doing a master of data science degree because that'll
give you some exposure to all facets of the data science field. A lot of masters of data science
degree actually don't let you do the degree unless you've got some technical background. So to
counteract this I'd recommend doing a diploma of data science which is actually better because that
lets you taste what data science is like and trial it to see whether or not you actually like it. So
once you've done the diploma you can then go on to doing a master of data science degree which
you might actually finish earlier because of your diploma of data science which gives you credit
towards your degree. Sometimes if you're really lucky you might be able to score an internship
or a job just through the diploma of data science. The final type of bachelor's student wanting to do
the master of data science are bachelor students that are looking to immigrate into Australia. So
getting a job as an international is very hard in Australia. Doing a master of data science degree
in Australia will give you a student visa which allows you to stay here for the duration of your
degree and during that time you'll be able to do internships and make your network in Australia
which allow you to eventually get a graduate job. And doing the master of data science degree also
means that you'll be able to secure a 1.5 to 2 year graduate visa upon finishing your degree. So
it's a great option for a bachelor student looking to immigrate into Australia especially if you
don't have enough experience. Now let's talk about the mid career transitional. So there will be
two types of mid-career transitioner, those coming from a stem field and those coming from a non-stem
related field. So first off if you're a mid-career transitioner that's in a stem-related field
such as software engineering then you don't really need to do a master of data science
degree because you can leverage your software engineering skills to get a position as a data
engineer or an ml engineer which will be your way into data science and you can learn all of
the theory of data science in your own time. And if you're interested in self studying data science
then I've got a 3 month roadmap to learning data science and it's completely free. Now if you're
a mid-career transitioner with no background in stem then you definitely should do a master of
data science and usually these degrees tend to be quite flexible which means you can do it part-time
alongside your full-time job and this will make the transition into data science a little
bit easier. In summary don't do a master of data science degree if you've already got a bachelor's
degree in a solid stem-related field. So the master of data science degree is best for non-stem
bachelor students, overseas bachelor students and mid-career transitioner with no experience in
STEM. Now finally if you're thinking of doing a master of data science degree in order to get a
promotion or a pay rise then save yourself the effort. It's a lot better if you just try to
level up in your existing job or try to look for other job opportunities which helps you level up.
That's it for this video if you enjoyed it then smash that like button and I'll see you next time.