Barely a week goes by without another set of battle lines being drawn in the war of future education. Fast moving disciplines (or collections of disciplines) like Data Science are quite rightly at the forefront of that war.
What got us a job in the data field five years ago is unlikely to be enough to get us a similar job today. That goes double if we haven’t kept our skills fresh and our eyes on developments across the whole DS spectrum.
That leaves those of us currently working as seasoned data professionals on the hamster wheel of continuous skill development, both inside and, more likely, outside of our working day. Beyond the burden of finding the time, energy and direction to pursue these new skills, we also have the choice of how how to get this education.
Never mind R vs Python or AWS vs Azure, our first choice has to be the method of learning: old school (in-person, trusted institutions) vs. new school (the potential Wild West of MOOCs).
Data Science Consultant Nic Ryan nailed his colours to the mast with a blog post on his Data Friends blog. Nic credits MOOCs with getting him interested in data science in the first place and getting him to where he is today. (If anyone isn’t familiar with Nic and his work, check out his appearance on Kirill Eremenko’s SuperDataScience podcast).
Nic’s background is in actuarial science. When he wanted to move into data science he realised he had the two choices above. Going the traditional route of back into studying full-time would have meant giving up the sole income his family was operating on (which wasn’t an option for obvious reasons) or use MOOCs to build his skills through online learning.
He went with MOOCs as they offered a more cost-effective and higher quality learning path than going back to university would have been able to give him.
It’s not just the ticket price of tuition fees, it’s the opportunity cost of dropping out of employment for a couple of years to pursue an academic qualification that may not give you the actual skills you will need at the end of it. The piece of paper you get is nice but it’s not much use on the first day on the job. Practical, up-to-date skills based learning in a MOOC is the opposite.
I’m a big believer in Lifelong Learning. Whether it be reading books and articles, taking courses or attending meetups and talks, there is something to be said for soaking up the value of other people’s knowledge and experience, regardless of what age you are. There has never been a better time for all of the world’s knowledge to be available to those of us lucky enough to have an internet connection and a connected device.
It’s all there for us. MOOCs are the large scale embodiment of that available knowledge-base so why wouldn’t we utilise them to their full potential?
I’ve written before that the biggest problem with MOOCs is that we don’t actually use them to their full potential. Anecdotally, it’s accepted that little more than 2% of MOOCs started are ever properly finished. I know I’m guilty of leaving a few in the 98% part of that. Self-managing your education means not having the same level of accountability over completing projects, lessons and tasks as you would have with actual tutors and deadlines to meet.
Without that accountability it also means that it’s somewhat easier for unscrupulous characters to claim that they’ve completed many MOOCs when they may not have quite made it to the end of the course (or anywhere near it in fact). That severely reduces faith in equating MOOCs with traditional training courses or learning qualifications in the eyes of many employers.
It’s hard to see how that can be overcome even with a growing number of MOOCs offering certificates and accreditation like nanodegrees for actual completion. The value just isn’t there amongst most HR departments when it comes to viewing these as actual credentials. And that’s a major problem when you don’t have a degree or Master’s underpinning your MOOC education.
That being said, MOOCs do give us an opportunity to build and hone new skills that we may not get in our day-to-day jobs. Tech platforms and infrastructure in companies can make it difficult to implement every cutting edge technology we read about in Towards Data Science or KD Nuggets. Signing up for a MOOC on Coursera, Udemy or LinkedIn Learning can help provide us with the necessary entry into a new area which we wouldn’t otherwise have been able to get.
If MOOCs are still in the infancy of their credibility when it comes to the data science job search then isn’t it enough that we use them for ourselves and our own learning rather than to impress a potential employer? I think so. If resting on your technical laurels is good enough for you then I would question why you picked a field like data science to work in in the first place.
Of course, new technical skills only really get properly included in your personal toolset when you get to use them regularly in your job. That applies just as much to traditional in-person course learning as it does to MOOCs so it would be unfair to use this against the online learning options alone.
You’ll see I’m back and forward on the question of just how valuable MOOCs are when it comes to getting people into a data science job. Maybe the credibility issue will be worked out over time as we see more and more people taking advantage of the lower cost and higher quality offerings from MOOC providers.
As the data science field matures and some of the data scientists of today become the hiring managers of tomorrow, we may see a move away from reliance on often outdated university courses and teachings anyway. Until then it’s hard to see how we can get away from advising new entrants to get at least a Bachelor’s degree to base their future learning on.
On a personal level, I don’t see any downside to pursuing further education at any stage of your career. In a rapidly changing world like data science, MOOCs can keep you closer to the cutting edge at a fraction of the cost and under the tutelage of some of the world’s finest DS minds.
You do have to actually do the work though and push on through to complete the courses.
Even better is to take those new skills and put them into practice on a personal project you can point future employers to on your own personal site, Github or Kaggle. Learn for yourself but don’t be afraid to let people know what you’ve learnt.
There are no prizes in this game for hiding your light under a bushel. If you have the skills on the job, I doubt anyone will ultimately care where you picked them up, just that you have them to call upon when needed.
(Photo by Raj Eiamworakul on Unsplash)