Guide


College vs Data Science Bootcamps

By Jess Feldman
Last Updated August 5, 2021

Many students intent on getting a data science job are bucking the traditional 4-year degree in favor of attending a data science bootcamp. Bootcamps offer many advantages, such as hands-on job experience and dedicated career services, but can a data science bootcamp really replace a college degree? Chester Ismay, Director of Data Science Education at Flatiron School, breaks down the differences between college and a data science bootcamp, what you can expect to learn in either path, and the kinds of jobs bootcamp graduates and college graduates land when they graduate.

Meet The Expert: Chester Ismay

How did you become a data scientist, Chester?

I was a Mathematics major and a Computer Science minor in my undergraduate years at college. I taught recitation sections as a TA helping out other undergraduates for three years, and I enjoyed working with students and helping them learn. I didn’t actually enjoy programming until about 10 years later. 

When I was at college, I didn’t realize there were more options to working with data than doing the traditional higher ed route. After I graduated with my master’s in statistics, I wanted to become a small liberal arts college Statistics professor, and the only way to do that is to get a Ph.D. When I was doing my Ph.D., I was introduced to more programming that solved statistical problems more efficiently.

As a college statistics professor, I eventually worked with students to get them up to speed on programming, which made me even more intrigued with data science. I taught an introductory data analysis class, and I was helping faculty and students with their data projects and getting them into programming. Soon after, I started transitioning away from a traditional academic professor role. For the last few years, I worked as a corporate trainer leading data science and machine learning classes for adults. Flatiron School’s data science bootcamp was the next step up!

Data Science Bootcamp vs College

Chester, as someone who took a more traditional route into data science (math + computer science degrees), do you think it's possible to learn data science at a bootcamp? Can a data science bootcamp be a replacement for college?

Definitely! A bootcamp can teach you the skills and ways to think about data science to get the ball rolling and start thinking about data problems effectively and efficiently. It depends on what a person is after, but if they want to get into the data science field and start building projects on the things they are most passionate about, I think the bootcamp style makes a lot of sense.

The Time Commitment + Cost

I think the biggest difference between learning data science at a bootcamp like Flatiron School versus in a college degree program is the time component and cost

  • Typically, you can expect 4 years for a college undergraduate degree versus 3 months for an immersive data science bootcamp experience. 
  • In a traditional, 4-year college degree, you’re not just taking data science classes. You’re taking classes such as sociology, literature, and philosophy and doing all of the other things that go into the college experience. 
  • When you’re learning in a bootcamp, you’re focused on data science and getting the practical skills needed to be successful in quickly landing a job in data science after graduation. 
  • In a data science bootcamp, there’s a bigger focus on the business problem itself. Business use cases are important because they prepare bootcamp students to adapt quickly to an industry role.
  • The average public, 4-year college degree costs $37,640 for in-state students and $95,560 for out-of-state students. On the other hand, the average bootcamp tuition is ~$14,000 total. 

Takeaway: The average data science bootcamp takes ~15 weeks to complete (and maybe another 3-4 weeks to complete the Pre-Work). If you want a well-rounded college experience, that will take 4 years (and maybe another 6 for a PhD). 

What You’ll Learn in a Data Science Bootcamp vs College Curriculum

Can you even get a “data science degree” in college these days?

College has changed a lot, and some colleges and universities have begun offering a bachelor’s degree in data science. College graduates are also going back to get their master’s and Ph.Ds  in applied mathematics, computer science, or statistics as well. That said, I think universities face challenges in trying to understand what content to teach college students, striking the right balance between statistics and computer science, and how many data science classes they’re going to offer. Teaching all of the skills needed for data science in a four-year program rather than a 15-week immersive bootcamp can be challenging. 

What does a data science bootcamp curriculum cover versus a college degree program?

A college degree is going to give you a lot of the theory whereas a data science bootcamp is going to teach you theory as needed. At a data science bootcamp like Flatiron School, we’ll point you to resources to give you a theoretical background, but we’re more focused on teaching practical skills and business use-cases with hands-on projects and assignments. 

Another difference is that Flatiron School has a central data science curriculum team that is constantly improving the curriculum. Our data science bootcamp curriculum was designed by reviewing the skills and knowledge that employers were looking for most. We designed it backward by understanding the skills employers are looking for and how we can incorporate that best into the curriculum. As the field changes, we’re iterating and adapting to ensure bootcamp students are prepared for success in the real world. 

While there are curriculum creators at some colleges, a professor typically writes their own curriculum content, which means they review the content, they teach the content, and they grade students on their performance throughout. 

Takeaway: Colleges teach theory with some application, while bootcamps teach practical applications with some theory. Typically, bootcamp curricula are based on industry needs while college professors define what they teach in their own classes. 

Teaching Style at College vs Data Science Bootcamp

Teaching Style at Flatiron

Flatiron School has a central lecture model where a central lecture team delivers content live to our live program students. Giving the lecture live online means that Live program students hop into a classroom and see the instructor or lecturer teach those classes. Our lectures are recorded so Flex program students can observe lectures on their own schedule and Live program students can also review those lectures at a later time if needed. We also have instructors on site at different locations and virtually to help students with the pacing of content by answering questions and checking for understanding beyond what a lecture is able to do. 

Student Progress + Exams

At a university you would expect exams, quizzes, and maybe some projects. There is a lot of focus on testing for learning via assessment without the opportunity to respond to feedback as often as one might see in their career. 

At a bootcamp, we are much more project-based than a college program, and we don’t give exams like in a traditional academic program. In a bootcamp, we’re trying to simulate the business experience that students can expect in their future data roles. We have frequent check-ins where students get to talk with their peers or an instructor acting as a manager, just as they would check in with a manager on the job to see if the prerequisites are being met for a project. 

All Flatiron School bootcamp students complete a 2-3 week comprehensive capstone project. For these final projects, students work in groups to coordinate, improve, and make little tweaks along the way. At the end, they present their findings in a report as well as a presentation. 

The Takeaway: Expect mostly tests and exams in college; at a bootcamp, your competency is tested through standup meetings, group projects, and a final capstone project.

The Ideal Student for Each Path: Bootcamp vs College 

Is there an ideal student for a data science bootcamp versus college?

To be successful in a data science bootcamp, you have to be motivated to work hard and be as efficient as best as possible, with determination and grit. A bootcamp is usually around 15 weeks long – it will go by fast! That is different from the standard classroom setting; bootcampers have to learn content and apply it as best as they can. 

If you’re looking for the friendships and relationships that can grow over the course of four years with a college experience, then a university path may be for you. A data science bootcamp is the way to go if you want exposure to this field and to explore whether data science is the career you want.

I’ve seen people all across the age spectrum in a bootcamp, from younger, college-age folks to more experienced folks that are deciding to make a career change or upskill. You can participate in a bootcamp for around four months and get the skills needed to land a data job without a college degree. 

At Flatiron School, we want to help people that are passionate about data science. These could be people who are brand new to data science or those upskilling. Having previous knowledge of a business can be a valuable asset in framing problems and setting expectations for projects. 

College applicants have to take the SAT, apply to universities, etc. Are there prerequisites to get into a data science bootcamp like Flatiron School? 

We always want to make sure students are prepared and at the same level when they get started in the bootcamp, so all of our students complete pre-work. It gives our students a nice foundation to make sure everyone’s on the same page. The pre-work prepares students for programming in Python, helping them understand statistical terminology, and starting to look at data visualization

Could a data science bootcamp replace an advanced degree for someone who already has an undergraduate degree?

Definitely! I’m teaching some bootcamp students right now with mathematics and computer science degrees. They have enrolled at Flatiron School because they want to understand data science business use cases or what a machine learning problem looks like. For those bootcamp students with advanced degrees, we give them plenty of relational skills in addition to Python programming skills. We teach them how to interpret their results and how to appropriately set up problems.

The Takeaway: Data science bootcamps can give students with an undergraduate degree the business use cases, Python programming, and machine learning knowledge they need to further their data careers.

Which Jobs Can Bootcamp Grads Land vs College Grads

Our data science bootcamp graduates go on to become data scientists and some become data engineers. Some graduates also take jobs as data analysts, business analysts, pricing strategists, healthcare analysts, and geoscientists. In the last group of our data science cohorts, there were 50-60 different job titles! 

This is a very exciting time for data science and I think we’ll see a trend of roles that use data but don’t even have “data” in the job title!

These are the same job titles that you would expect after graduating from college.  

What should a student expect from a university career services team?

Universities do offer career services that can help students work on their resumes, but I think it’s a much more immersive career support experience at Flatiron School. At college, career services might be happy to see students succeed, but there isn’t as much interaction with that career services team unless a student reaches out to them. 

How is that different from a data science bootcamp’s career services? For example, what kinds of career services can Flatiron School students expect?

Flatiron School students have a dedicated career coach and those career coaches help students build an online portfolio and their own unique brand. Career services gives our students a lot of interview practice, from technical interview questions to behavioral interview practice. Career services help students understand the things they should be saying and the work they will need to do to prepare for those interviews. Career coaches meet regularly with students while they’re on the data science job search and they check in on their progress. Career coaches are here to help students craft job materials for specific job ads and help them be as successful as possible. We also have an employer partnerships team who work with employers to build relationships and help find great matches with our students. 

Find out more and read Flatiron School on Course Report. This article was produced by the Course Report team in partnership with Flatiron School.

About The Author

Jess is the Content Manager for Course Report as well as a writer and poet. As a lifelong learner, Jess is passionate about education, and loves learning and sharing content about tech bootcamps. Jess received a M.F.A. in Writing from the University of New Hampshire, and now lives in Brooklyn, NY.

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