Guide to Data Science Bootcamps – Comprehensive listing of Bootcamps in the US

with Kat Campise, Data Scientist, Ph.D.

First, a word of caution regarding data science boot camps: while they can be a great way to dive into the data science world, they are not a replacement for the unique combination of academic training and practical application in advanced math, statistics, research, and experimental design, essential programming skills, and relevant knowledge in the target industry. It’s definitely true that most employers require at least a Master’s degree in a STEM field as a minimum qualification to be considered for their data science positions. Yes, there are exceptions where employers will review candidates who have a Bachelor’s degree. However, the applicant pool is still expected to have a STEM degree at the very least to get past any automated algorithm or human resource personnel that pulls out keywords from your resume/CV.

That being stated, in-person and online data science boot camps can help sharpen your skillset as you apply the knowledge, skills, and abilities required for extracting, transforming, and analyzing various data types. 

Boot Camps vs. MOOCs

In the flurry to meet the booming need for data scientists, boot camps and MOOCs (Massive Open Online Courses) rushed in to fill the gap. MOOCs are often free-form, which means you can attend them according to your personal schedule and are often spaced out over the course of several weeks, which means the content is more digestible. Meanwhile, boot camps are typically more intense because they involve a significant amount of information that is compressed into a short time period. If you are serious about learning more about data science and can handle this instructional format, a boot camp is an excellent option to consider. 

Data science boot camps have two delivery formats: in-person and online. Most are not inexpensive, ranging in cost from just under a thousand dollars to upwards of almost $20,000 for 8 to 15 weeks of instruction. Also, a majority (if not all) of the boot camps are project-based: by the end of the instructional term, you should have a completed project that clearly demonstrates your ability to complete a data science cycle using Python, R, SQL, Hadoop, Tableau, and accurately apply the appropriate statistical methods.

Some boot camps provide an introduction to enterprises seeking qualified data science candidates and/or boot camper projects are centered on working with those enterprises to solve a specific issue (thus boosting your opportunity to secure a job once the boot camp is concluded).

There is no difference between MOOC and boot camp learning objectives. You will be expected to learn all the usual data science things that can be taught (yes, there are aspects of data science that tap into intuition, which is developed from repeated practice within the discipline, and these can’t always be overtly taught).

However, MOOCs are far less costly — Coursera and eDX have data science learning paths that are freely available — and they don’t offer in-person instruction. As such, learners are self-directed and don’t have direct access to experienced mentors. For example, Coursera assignments are either auto-graded (e.g., multiple-choice questions, exercises using DataCamp, or another instructional partner) or the projects are graded by other students.

MOOC instructional design includes hands-on practice for both guided instruction (e.g. an already well-known dataset such as the infamous Iris dataset or mtcars), and a final project (note: depending on the MOOC, some of the final or capstone projects may be student choice — where you will use a data set of your own choosing — or you will be assigned a data set that is the same for all learners in the module). 

Determining if a Data Science Boot Camp is Right for You

It’s important to stop for a moment and ask yourself why you want to be a data scientist. Why? Because it’s a profession that has a high barrier to entry which translates into investing copious amounts of time and money. Sure, the salary is attractive — for the moment. But, depending on which company you work for (or even if you decide to try to start your own company) the salary might not be the six figures everyone sees posted on job search sites. Plus, if you work for a small startup, there will likely be the “many hats” problem. While this isn’t insurmountable, a newly minted data scientist who has visions of “doing data science” all day may be quickly disappointed. 

Therefore, it’s always essential to conduct extensive research on a boot camp before enrolling in one. Once you have obtained all of the primary information about a boot camp, evaluate your interests with regards to data science and use this to determine whether the program is a good fit given your career goals. 

Will a Boot Camp Help You Get a Job?

The other pertinent consideration is that while data science boot camps may look good on your resume, and you might be introduced to possible employers, they don’t replace the almighty STEM degree. Plus, many boot camps have prerequisites for entry, even if it’s only basic knowledge of R, Python, and SQL along with college-level statistics.

Are You Willing to Travel to an In-Person Boot Camp?

Not all boot camps have an online option available, and you’ll find that most U.S.-based boot camp providers have a limited selection of onsite locations (of course, if you live in those locales, then this isn’t necessarily a problem). Also, many of the boot camps are full-time immersion programs where you’ll be in class or attending various meetups and events every day, five days a week, for the entirety of the boot camp. This is great for networking and mingling with data scientists who are already in the industry. But, if you need to work full time or don’t have a lump sum of money stashed away for living expenses, then the pricey in-person data science boot camps might not be an option.

How Much Money Can You Spend?

Finally, the cost. There are less pricey boot camps, such as DS3 which is free. In-person data science boot camps will, naturally, require that you travel to them; so, there is an additional financial outlay, however small that might be. The more advanced boot camps vary in price from $1,500 to $16,000.

Fellowship-based programs do exist: Insight Health Data Science, Silicon Valley Data Academy, and The Data Incubator are a few prominent examples. You will need to look closely at their entry requirements. The Data Incubator, for example, only accepts program applicants who are, at most, within 12 months of graduating with either a Master’s or Ph.D. in a STEM or social science field. But, on the upside, they do have some high-level hiring partners which include (but are not limited to) Pfizer, JPMorgan Chase, and Microsoft. 

Consider This as Data Collection

This information is not meant to deter your data science journey in any way, shape, or form. On the contrary, the goal here is to ensure that you are carefully investing your time and money into a career trajectory that is still evolving. There is still a tremendous amount of hype saturating data science, and all too often the talking heads on social media recommend a data science career merely based on the blog links floating through their timelines: Data Science Shortage! Data scientists dig deeper and ask why that might be true (or untrue). So, it behooves you to start practicing data science and consider this as one part of your data collection process for determining whether or not you have the interest, time, and money to meet the cognitive demands of being a data scientist.