Are Data Science Boot Camps Worth It? A Simple Breakdown

Data science is amazing; the modern world runs on information! Today, just about every industry has incorporated Big Data and data analytics into their operations. Retailers assess trillions of customer decisions to figure out which products to stock; manufacturers use data to bolster production line efficiency; real estate magnates use data to figure out where and how people will live. 

Data-driven decision-making has become so inherent to modern business that not using analytics is like attempting to navigate a maze while blindfolded — it’s a quick way to get stuck in a (money) pit.

The indispensability of analytics has made data science a lucrative and high-potential career for any math-minded professional — and these days, it’s easy enough to train for the field with a short-term boot camp program. But are data science boot camps worth it?

It’s a decent question; after all, aspiring data scientists need comprehensive training. In their day-to-day work, data scientists are responsible for combing through troves of data for actionable insights. These professionals create and apply algorithms to expansive data sets, then assess the trends they find to derive business-applicable conclusions. It’s an intense career  — can boot camps prepare newbie professionals to meet the challenge?

Our answer is a resounding yes. In this article, we’ll cover every question you might have about these popular programs, from explaining how they operate to what you’ll learn.

So, are data science boot camps worth it? Let’s discuss.

How Data Science Boot Camps Operate

First, let’s cover the basics — what is a data science boot camp, exactly?

Data science boot camps are short-term, intensive training programs that equip learners with in-demand industry knowledge via project-based learning. The majority take between three to six months to complete and cover topics such as programming, predictive analytics, statistics, data visualization, and general data analysis. 

Besides building a strong foundation in statistical and analytical thinking, boot camp learners learn a variety of highly marketable and industry-relevant technical frameworks. These technologies often include but are not limited to: Python, SQL, Hadoop, Spark, and the Pandas/NumPy libraries. 

Many boot camps are flexible enough to accommodate for part-time, full-time, in-person, or virtual learning experiences; however, boot camps will differ in their cost, expected time investment, class sizes, and background knowledge requirements. You’ll want to carefully compare different programs to see what works best for you before enrolling. 

Full-time schedules generally require five 10-hour days per week of learning, coding, and collaborating on projects. In contrast, part-time programs allow learners to balance their classes alongside other personal or professional obligations. Part-time coursework makes it easier to have a life outside of the boot camp; however, choosing a more flexible schedule can extend a learner’s upskilling time to twice that of a full-time learner. 

Depending on the boot camp, learners may have access to valuable career services upon graduating. Interview prep, peer networking resources, and career coaching are all common resources that quality boot camp programs offer. Learners also benefit from one-on-one communication with knowledgeable mentors and collective communication with other aspiring data analysts. 

In recent years, the boot camp model has become increasingly popular among learners, particularly in the software development sector. While there is limited data available about data science boot camps specifically, the coding boot camp market’s runaway growth suggests that there is great potential for similar programs in data science. 

In a recent report, Verified Market Research valued the global coding boot camp market at $399.91 million in 2018 and projected that it would top $889.37 million by 2026. This expansion is already evident; a whopping 33,595 learners graduated from boot camps in 2019 alone — a 4.38 percent growth in enrollment since the year before. 

Are data science boot camps worth it? Thousands would say yes. For many learners, boot camps provide one of the only viable paths into an industry that would otherwise require years of costly study. A college education just isn’t feasible for people on a budget or those looking to pivot careers. 

Successful boot camp graduates have the potential to become data scientists or data analysts for any industry that interests them. 

What They’ll Teach You

In contrast with traditional four-year degree programs, data science boot camps tend to focus more on equipping you with skills you will need once you hit the labor market. While a college education might have an intense theoretical focus, most boot camps focus on the specific tools and technologies you’ll need to hit the ground running.

Data science boot camps typically cover data science programming, cleaning and analyzing data, data modeling, visualization of data, and research presentation. The vast majority use Python as the primary programming language, given that it comes equipped with code modules that are well-suited to addressing machine learning, artificial intelligence, and analytics processes.

Languages and Tech You Might Learn*

• SQL (Database management)
• Python
• Statistical analytics libraries, like Pandas, Matplotlib, and NumPy
• Hadoop
• R
• Front end languages: JavaScript, HTML, and CSS

The Concepts You Might Cover*

• Statistics
• Machine learning
• Research design
• Presentation and communication
• Big Data

*These lists provide a general outline of what a boot camp might cover. For a clear understanding of the skills and capabilities taught by a specific program, ask to review its curriculum. 

Is Any Prerequisite Knowledge Required?

Generally, no, you won’t need to have prior knowledge of data analytics to enroll in a boot camp. Some programs don’t even require their learners to hold a high school diploma. 

That said, a few of the more advanced programs will ask learners to have a foundational grounding in data science and analysis. It’s not entirely unheard of for data science boot camps to require a bachelor’s degree in one of the STEM disciplines (science, technology, engineering, or math) — though, again, this is relatively rare. 

Before you join a course, we recommend brushing up on basic statistics and mathematical concepts. Look into what, if any, prerequisite knowledge the specific boot camp program you’re applying for requires, and check to see if it asks learners to complete any pre-course study on foundational concepts.

Additional Resources:

• How to Learn Math for Data Science, The Self-Starter Way — Elite Data Science
• Data Analysis 101 — Khan Academy
• Statistics: A Full University Course on Data Science Basics — freecodecamp 

How Is Coursework Structured?

No two boot camps are the same — but there are a few widespread structural trends. 

In recent years, hands-on learning has become very popular among boot camp programs. This model emphasizes the importance of creating real-world analytical projects from actual data sets that you’re interested in.

A hands-on course may help you develop a project that requires you to apply the concepts you learn as you proceed. You may start by cleaning the data, developing a hypothesis about the results, and then finally modeling the data to disprove (or prove) that hypothesis. Afterward, you might even create a compelling visual model that can present your insights meaningfully.

Project-based courses provide you practical knowledge about the way professionals deploy data science technology on real assignments. Best of all, this approach ensures that learners can graduate from their program with a compelling portfolio project. 

Alternatively, some boot camps may emphasize the understanding of theoretical frameworks over specific technologies. While project-based learning still tends to live front and center in the boot camp sector, these alternative programs make the case that learners should learn how to learn so that they can pick up specific data science skills on their own. 

In a field as frequently in flux as data science, we can’t understate the importance of becoming a robust learner. Consider what type of program would best suit your learning style before settling on one choice!

Can Data Science Boot Camps Help You Land a Job?

The short answer? Yes.

Right now, data science is experiencing a significant talent crunch. Quant Hub reports that a full 67 percent of surveyed companies are expanding their data science teams; job listings for data science roles increased by 37 percent in year-over-year growth between 2018 and 2019.

“Companies are studying ways to democratize data science by upskilling and reskilling employees in the hopes of becoming less reliant on a small siloed team of expensive experts to see a return on investment in data science,” the report notes.

Interestingly, there are three times the amount of job postings over job searches performed about data science. In other words: more employers are searching for qualified candidates than there are job seekers who are looking for roles. Now, a staggering 83 percent of surveyed companies are investing in Big Data projects. As a result, the global tech talent shortage is expected to reach 85 million by 2030.

With such an intensive and protracted need for talent, employers are more than willing to take on skilled employees from different educational backgrounds. On the whole, employers are more concerned with what applicants know than where they obtained their knowledge.

While there isn’t great data available concerning data science boot camp hiring rates, we can find some indication of positive outcomes from coding boot camp statistics more generally.

According to HackerRank (PDF, 2.8 MB), nearly one in three (32 percent) hiring managers have onboarded a boot camp graduate. Moreover, 72 percent of those who have taken on a boot camp graduate state that those professionals are “equally or better equipped for the job than other hires.” Researchers for Indeed further found that 99.8 percent of surveyed hiring managers who have hired boot camp-trained professionals would gladly do so again.

The outlook for data science boot camp grads is sunny. With the right coursework and a standout portfolio, it’s more than possible to land a fulfilling role in data science.

Average Cost

Many individuals gravitate toward boot camps since they offer a relatively low-cost way to achieve a high-quality education.

There aren’t many formal reports on how much data science boot camps cost but we can get a sense of cost trends by reviewing the coding boot camp sector. According to Course Report’s 2020 Coding Bootcamp report, the average boot camp program costs $13,548 in total. 

Plus, most boot camps offer some payment flexibility. Some boot camps provide scholarships. Meanwhile, others offer payment plans to allow learners to pay back their tuition fees in manageable installments over time. 

With so many payment flexibility options, boot camp costs are typically manageable for learners of all economic backgrounds. 

Final Thoughts on Data Science Boot Camps

So, are data science boot camps worth it? The answer is a resounding yes.

Considering the sheer volume of marketable skills that boot camps impart, as well as their growing esteem in the industry, data science boot camps are well worth it.

Data science exposes you to the unseen logic that guides businesses day in and day out. As an analytical professional, you could be responsible for delivering meaningful insights that completely shift the direction of an enterprise. If you have a passion for statistics, why not try your hand at the expansive world of data analytics?

Look into your options and consider enrolling in a boot camp program that works with your schedule, preferences, and budget.