A Better Way to Skill Up
By: Tony Yiu
Tags: Careers, Startup, Data Science, Technology, Education

The Problem with Education as a Service Today

Today’s education as a service offerings primarily focus on up-skilling. They try to teach you the in-demand skills of the moment so that you move in the direction of the gold arrow below — from unemployed and inexperienced hermit to knowledgable and employable working fellow.

Education as a service tries to move you in this direction

The problem with moving in this direction is that it’s really hard. It’s not enough to learn the stuff but you must also:

Obtain a credential that signals to employers that you are knowledgeable — and it must be a credential that they have heard of and respect.

Demonstrate the ability (preferably through actual paid experience like contracting or an internship) to practically apply your knowledge towards solving business problems. This becomes especially important if your credential is not top tier.

Do you see the problem? Everything is about earning credibility and there are currently only two primary ways to earn it — universities and companies. Since I write often about data science, let’s use it as an example. An aspiring data scientist trying to break into the field can earn some street cred in one of two ways:

Attend a respectable university and obtain a degree in data science (preferably an advanced degree). Convince a respectable company to pay you to work in a data related role.

MOOCs, bootcamps, and other alternative offerings, on the other hand, are unable to earn you the necessary credibility. They may teach you the necessary skills (in my experience, they do a pretty decent job at this). But it’s kind of like that old philosophy cliche:

“If a tree falls in a forest and no one is around to hear it, does it make a sound?”

Even if I developed a deep understanding of machine learning and statistics through reading books, blogs, a MOOC or two, and a bootcamp, I would still probably get rejected from the job I want. Employers just don’t put much stock in a certificate of completion.

And it is a gamble from the employer’s perspective: given that you have no data science work history and no one to vouch for you that you truly know your stuff, they can only take you at your word. And unfortunately not every employer is willing to do that — people, including hiring managers, are generally risk averse and willing to pay a premium for the safe, “proven” candidate (hiring the wrong person is painful from both a productivity and financial perspective).

Yes I know. If you are full of drive and initiative, you can place in Kaggle competitions, meet industry insiders at conferences and meetups, build up an awesome portfolio of data science projects on your own, and work pro-bono for an early-stage startup (all while interviewing). But that is not for everyone. Bootcamps and their education as a service competitors, while cheaper than a traditional college degree, still cost a fair bit in terms of time and money ($15,000 to $20,000 in tuition and at least months of your time). They also emphasize in their marketing how employable you will be upon graduation. But without connections or a prestigious enough certification (which even the best bootcamps lack), your completion of the program is just like a tree falling in a deserted forest with no employers around to see it or care about it.