Easy to Get in Data Science Masters
Why You Shouldn't Take a Data Science Masters Degree
…and what you should do instead
As the job of Data Scientist has become increasingly popular over the last few years, helped by being crowned "sexiest job of the 21st century", Masters degree courses specialising in data science have sprung up. The cost of these courses can range anywhere from $30,000 to $100,000, not including the cost of living whilst you take the time out to study.
My own route into data science did not include any formal education. I taught myself the skills I needed through self-study using free or very low-cost resources widely available online. In total, I would estimate that I spent no more than $300 on paid material.
Having recently been sifting through CV's and interviewing candidates for data scientist positions I have come to the firm conclusion that Masters degrees in data science are not the best route into the field. It is just a very expensive way to learn the skills you need, and it won't even teach you everything you really need to know.
In this article, I am going to give you the key reasons why I feel that taking a Masters in data science is not a good route into the field and why a self-study route is, in most cases, a better alternative. I will also give you a brief overview of what you should do instead to land a job as a data scientist.
They are expensive
As I mentioned above Masters degrees are very expensive. They also require you to study over a certain timeframe, which can make them even more expensive, as you don't necessarily have the option to work and earn a living alongside your studies.
This is ok if you have the means to fund a degree and pay for your living costs at the same time but the reality is that many people don't have the ability to do this. This means that you either have to take on large amounts of debt to fund the course or that you simply cannot take it at all.
The good news is that these courses are absolutely not necessary to become a data scientist and you can learn everything you need to know, and most importantly land a job, without spending a small fortune in the process.
They don't teach you everything you need to know
Working as a data scientist does not just require a knowledge of statistics, mathematics, programming and machine learning theory. Actually performing well in a real-world data science team needs many skills beyond this which are not taught on the majority of Masters degree courses.
These courses will not teach you how to use Github and why it is so important for working collaboratively within a team with not only other data scientists but data and software engineers as well. They don't teach about agile, a process used by many data science teams. They don't teach you vital soft skills such as communication, creativity and business acumen that are extremely important for a career in data science.
I have interviewed many candidates with data science Masters degrees who have little to none of these skills that are highly valued by most companies. These are skills, that if you learn data science through self-study, you almost certainly will pick up along the way.
Data science includes many disciplines
To succeed as a data scientist, you need skills from several disciplines, including mathematics, statistics, and computer science. In my opinion, it is difficult for a data science masters degree to adequately teach skills from all of these fields in enough depth. A 1–2 year course isn't going to prepare you enough to land a job as a data scientist.
Data science takes many years to master largely because it is an amalgamation of many different fields. Learning through self-study and through jobs in related fields (which I will cover a bit later) will give you the depth you really need in all these different areas.
I don't disagree with taking a Masters degree in general, and in fact, I think they can be a great way to get deeper knowledge in a specialist area. I would personally advise, for data science, that you take a Masters in just one of these fields such as computer science or statistics, for example. This will give you a valuable depth of knowledge in this area. This would also provide a great foundation for studying the remaining areas of data science.
What should you do instead?
As previously discussed my personal view is that you can study everything you need to learn data science for free or at a very low cost online. The added benefit of doing this is that you can learn at whatever pace suits your circumstances. So if you need to hold down a full-time job or have other responsibilities then you can fit your study around this and take as long as you need to learn the skills.
In addition, you can also study in a way that suits you best. I personally learn best through practical learning so I took a project-based approach to my learning from day one. This is not necessarily something I would have been able to do via a Master degree course.
In addition to self-study, I would strongly recommend that you try to gain some practical experience of working with data or software in a real-world setting. This could be achieved through internships, volunteering, hackathons, contributing to open source projects, or getting positions in closely related jobs such as business insights or analytics. This will give you exposure to the realities of working with data and tech and give you demonstrable experience that will eventually help you land a job as a data scientist.
This article is based on my own personal experience of learning data science and also of personally interviewing candidates for data science jobs. These experiences have taught me that demonstrable skills, in the form of a portfolio of projects or related work experience, hold much more weight than certificates and qualifications, when it comes to actually get a job in this field.
This is why I personally recommend learning data science through self-directed study and practical real-world experiences. What is particularly good about this approach is that it means that anyone can get into the field and that finances are not a barrier to people entering into data science.
If you want to find out more about how to study data science for free online and where to find resources I previously wrote a comprehensive guide which can be found below.
Thanks for reading!
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Source: https://towardsdatascience.com/why-you-shouldnt-take-a-data-science-masters-degree-c40c2f02f1e1
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