Where Do Data Science Bootcamps Go From Here?
By: Tony Yiu
Tags: Machine Learning, Data Science, Technology, Careers, Education

So What Can Bootcamps Do?

Unfortunately, there’s no easy solution. Health and safety come first. And in a world where every bootcamp is online (at least temporarily) and there are fewer data science job openings, bootcamp providers will need to accept the fact that their service is simultaneously of lower value and in less demand.

So price declines (and consolidation) are probably inevitable. At the same time, for the intrepid and diligent bootcamp providers, the next year or so represents a significant opportunity to change for the better. The data industry is not as hot as it once was — companies desperate to cut costs in the face of lower revenues will keep their software engineers (as they keep the lights on) while laying off staff that sit further from the frontlines of the business (like data scientists).

This doesn’t mean that the need for analytics or data driven insights is gone; just that it’s been put on the back-burner or deemed too high cost to pursue at the moment.

That’s an opportunity for bootcamps and their students to step in.

On one side, you have companies interested in data science but without the budget to pay market rates for full-time data people. On the other, you have data science learners chomping at the bit for actual, practical experience, and who are willing to do it for a small fraction of the market rate. So why not restructure the bootcamp experience to help meet this need?

The Current Format

Currently, most bootcamps comprise 3 months of instruction (and project work). There are 4 to 5 projects, which form your project portfolio and become the data science bullets on your resume. And the final project is usually accompanied by a presentation to hiring partners. After the bootcamp, there are weekly or bi-weekly checkins with career services, but besides that, it’s up to you to keep up with your job hunt.

One thing you might not know going in though is that most of the formal instruction and lectures conclude 2 months in, and the last 4 weeks are primarily for working on your final project and interview practice. Yes, the last few weeks of the bootcamp are kind of like a study hall (though instructors and teaching assistants are around for questions).

A Better Format

Current vs. proposed format

The way I imagine it, the bootcamp would be 4 or 5 months long instead. During the first 2 months, the focus is to skill up the students while the second half is for student teams to work on data science consulting engagements with actual companies.

There are two downsides for bootcamp providers. First, a longer bootcamp means that a given location can only graduate 2 to 3 cohorts a year instead of the current 4; so all other things equal, providers would earn less money. And second, providers would need to do more legwork in advance of signing up a cohort — they would need to line up companies and projects for their incoming students.

But while challenging, this is also an opportunity for significant differentiation. Currently, the bootcamp industry is becoming more and more commoditized (putting downward pressure on price). So doing nothing will also lead to lower revenues. But if a bootcamp can demonstrate value by lining up lots of interesting projects, then they can charge higher prices.

And this gives the bootcamp providers’ career services employees a more targeted objective. Currently, the career services employee occupies an odd role that’s part cheerleader, part networker (attempting to build connections with corporate recruiters and hiring managers), and part college job counselor (revising resumes, doing mock behavioral interviews, and polishing up students’ LinkedIn profiles). That’s a lot of jobs and it’s hard to do them all well simultaneously. Compounding this challenge, each bootcamp location usually has only one career services person and he or she needs to not only manage the job hunts of the current cohort but also the ongoing job hunts of all the previous cohorts as well. In my proposed structure, career services employee would go from a jack-of-all-trades type to a specialist specializing in building connections with companies interested in data science consulting (and a pipeline of cool projects).

If the bootcamp provider and its employees can do this successfully, then it puts its students in better positions to land jobs (as they have real experience with actual companies) and differentiates its product from its online-only peers.

Obviously, all this would work better in-person but data science consulting remotely works too. It’s not so different from an expanded version of the take-home assignments companies like to give candidates (where they throw candidates a dataset and some open-ended questions and ask them to do their best).