Here’s Why a Bootcamp Won’t Make You a Data Scientist

Data Scientists
Shutterstock Licensed Photo - 1880995645

Bootcamps are en vogue in all sorts of industries, with the idea being that intensive training over a short period can bring newcomers up to speed with complex concepts in a flash.

This sounds good in theory, and in many contexts, it has a lot of clout. But the field of data science isn’t exactly suited to the quick and dirty approach to employee education.

Here’s why.

The competition is fierce

The first issue is that if you want to apply for positions which require a data science background, then even if you’ve undertaken a bootcamp, you’ll be competing against candidates with much more impressive qualifications.

That’s why bootcamps offer benefits in certain career paths, and not in others. For example, if you complete a front-end developer bootcamp at, you’ll be in a stronger position to succeed when applying for jobs later on.

Data scientists, on the other hand, tend to have Masters-level education in a relevant subject under their belt, even if the role they are aiming for is on the bottom rung of the corporate ladder.

If you’ve already got a Masters, then a bootcamp could be a great way of refreshing your knowledge and skills. But don’t expect to stand out from a stack of resumes if a bootcamp is the only relevant certification you’ve attained.

The mainstream narrative is deceptive

Another issue facing data science at the moment is that there’s a lot of misinformation out there about how accessible the field is.

Read articles, watch videos or check out training course marketing and you’ll get the impression that this is a specialism that almost anyone can attain. Furthermore, it’s implied that you don’t need to work particularly hard to enter the echelons of data science.

What this doesn’t make clear is that only a tiny proportion of data scientists were able to get a job when starting from scratch in 12 months or less.

The majority spent years earning degrees, gaining experience and cutting their teeth in different roles before finally reaching the point where they could go pro. And so again, a bootcamp will only work wonders for those with a solid grounding in the right skills and knowledge already at their disposal.

The breadth of data science is a sticking point

While the term ‘data science’ is bandied around regularly, it’s worth noting that there’s not a single subset of areas that it covers, but rather a multitude of potential paths to take.

Because of this, no bootcamp or short-term training course can possibly encompass every conceivable facet of what goes into making a data scientist, because there simply won’t be the time.

A true data scientist will need to combine the training they receive with their own, self-guided learning. This has been the way of things for a long time and will remain the case indefinitely.

There are other stepping stones to take

A data science bootcamp can be a little like a get rich quick scheme, in that it promises the world but ends up falling short, and it’s only the fault of the participants if they don’t get where they want to be immediately.

The solution is to think carefully about your existing skills, as well as your circumstances, and see if there are different ways to gain data science-like experience without taking a course.

This might mean getting into marketing analytics, for example, in order to understand some of the tools and techniques which can later be applied to data science training. It’s about having realistic goals and knowing when claims are too good to be true.

Kayla Matthews has been writing about smart tech, big data and AI for five years. Her work has appeared on VICE, VentureBeat, The Week and Houzz. To read more posts from Kayla, please support her tech blog, Productivity Bytes.