2021 Data Science Bootcamps Guide

Ready to jumpstart your career in data science or looking to advance your current career by learning new data science skills? A data science bootcamp might be the right path for you.

 

What is a Data Science Bootcamp?

Data science bootcamps are intensive educational programs designed for adults looking to launch a new career in data science or a related field. They are classified as a form of higher education since most programs require students to have a high school diploma or G.E.D. However, they are not degree programs.

The ultimate goal of most data science bootcamps is to provide students with highly marketable technical skills for working with data, and then, to match them with employers who need to fill roles with skilled employees. To meet this goal, many bootcamps include career services like professional development support, networking opportunities, and mentorship. 

Data science bootcamps vary in duration depending on how much material is covered in the curriculum and how many hours of work there is per week. Most are between 10 and 36 weeks long and have a time commitment of about 15 to 40+ hours a week. In total, these programs take between 150 and 1,400+ hours to complete.

 

What Will You Learn at a Data Science Bootcamp?

Data science bootcamp curriculums always include one or more coding languages that are well suited to data manipulations, storage, and querying. Most teach Python and/or SQL. Bootcamps also teach students stats fundamentals and algorithms that can be used to help understand data. Advanced skills include forecasting, modeling, and using machine learning with large data sets. In addition to these techniques, students will likely learn other technologies like Matplotlib, Internet of Things, Automation, Tableau, ETL, JavaScript, and more.

Apart from technical skills and methods, some bootcamps include training on soft skills such as presentation-giving, interview practice, project management methodologies, and general communication. 

 

We Asked a Data Scientist: What Skills are Most Important in Data Science?

To get a better idea of the most important skills students should learn to prepare for a career in data science, we talked to Robin Linzmayer, Data Insights Engineer at Flatiron Health. Here’s what she said:

“In terms of technical skills, I write a lot of Python and SQL. I feel like you can always learn those skills, but the hardest things are asking questions and communicating with people who have a very different background from you. Since I communicate with technical people – far more technical than I am in some capacity – and with product people who are not as technical usually, I have to tow that line and think about “how do I communicate a technical finding to a product person?” and “how do I communicate a product question to people in technical terms?” That’s probably the hardest thing to do.”

Read the rest of our interview with Robin on our Resources page!

 

Where Can You Take a Data Science Bootcamp?

Data Science Bootcamps are available in both part-time and full-time capacities and can also be taken fully online. Some online programs are 100% asynchronous, meaning students learn the material from online resources and complete projects at their own pace. Other online programs include a mix of individual learning, classroom-style virtual lectures, and group work. 

In-person bootcamps meet at the program’s campus or a local university. These in-person formats do sometimes include ‘homework’ that students complete outside of classroom hours. Due to the growing popularity of these types of programs, you can find in-person bootcamps across most major U.S. cities, including Chicago, San Francisco, NYC and more

 

What Types of Data Science Bootcamps are Available?

Bootcamps may take place in-person at a campus, or online through virtual classroom portals. Many bootcamp programs offer both formats and teach the same curriculum online as they teach in person. 

Some bootcamps are full-time programs in which students work on projects, participate in group work, and watch lectures from morning to evening Monday through Friday – with breaks scheduled in, of course. This format is the most immersive and requires a serious time commitment. It is also highly effective in helping students develop a firm understanding of data science on an expedited timeline.

This full-time schedule would be difficult for anyone with a 9-to-5 job, other academic pursuits, or family commitments, so many bootcamps offer part-time options tailored to meet the needs of these students. Part-time bootcamps generally take place outside of regular working hours (on evenings and weekends) or run on a self-paced schedule, which allows students to fit the work in whenever they have the time to spare.

Beyond those factors, another element to consider is the program provider. Some courses are offered through higher education institutions that provide in-person instruction on campus and may leverage professors and educational resources affiliated with the university. Other bootcamps may be offered via third-party or individualized providers, taught at their own location or online. 

When comparing bootcamps, consider where you see yourself headed in your career and what you hope to achieve by completing the program. While curricula of individual programs might seem similar, each will provide a different experience. Take a moment to review our listings and browse the program’s “About Us” page to see if the particular subjects and curricula align with the skill sets you are looking to learn. 

 

Requirements for Taking a Data Science Bootcamp

Most data science bootcamps require students to go through an admissions process, but as long as students demonstrate commitment, it’s unlikely a bootcamp will turn them away. The process may require students to answer a few questions about their prior experience and future goals through an online form or in a brief phone call. For more advanced bootcamps, students may need to pass a skills assessment for admission. Sometimes students who do not pass a skills assessment are encouraged to take a pre-bootcamp prep program before moving on to the full bootcamp. There are also bootcamps that cater specifically to true beginners with little to no computing experience. These programs won’t turn anyone away based on skill level.

Most bootcamps require students to have a G.E.D. or high school diploma and many have an age minimum of 18. Few require any post-secondary education. Many bootcamps serve international students as well as U.S. students, though some financing options may be limited to only U.S. students (citizens, permanent residents, and DACA recipients).

 

How Much Do Data Science Bootcamps Cost?

Tuition prices vary across coding bootcamps. Some bootcamps cost as little as $500, while others can be as much as $30,000, or even more. You’ll find that most of the lowest-priced programs are ‘bare bones’ – that is, they won’t have as much one-on-one coaching and career support. However, that doesn’t mean the quality of the material is any worse! Meanwhile, many of the pricier programs have perks like job guarantees and employer connections. When choosing a bootcamp, students should consider how much extra support they anticipate needing. 

It should also be noted that many bootcamps have a variety of flexible payment options available. Some allow students to make monthly payments instead of paying the full tuition up front. Others offer loans and scholarships or will connect students with third-party loan and scholarship providers. Another way to pay for bootcamps is through an Income Share Agreement. This type of agreement allows students to pay for tuition after they have secured a post-bootcamp job, by sending a percentage of their paycheck to the bootcamp provider each month until they’ve completed payment. This option isn’t available at all bootcamps and the specifics of the agreement do vary across those programs that offer it. 

Overall, education can be one of the largest investments you’ll make, so bootcamps offer a number of ways to pay

  • Funding through personal savings (Pay out of Pocket)
  • Choosing a lending partner
  • Pursuing scholarship programs
  • Selecting an Income-share agreement and/or deferred tuition program
  • Seeing if your school qualifies for the GI Bill.

 

Are Data Science Bootcamps worth it?

We’ve outlined the costs of a data science bootcamp above. Now, let’s examine the benefits so you can decide if a bootcamp is worth it based on cost-benefit analysis. The major benefit for students who complete data science bootcamps is that they will gain marketable skills to use in a data science job. These jobs are high-paying (on average, $103,930/year in 2020), and often bring workers a high level of satisfaction. 

While data science jobs are quite desirable, they require an excellent understanding of data science principles and hands-on experience working with data. Data science bootcamps provide these things to students. 

When deciding if a data science bootcamp is worth it for you, consider your desired outcome. If you hope to end up in a great-paying and satisfying data science job, a bootcamp will likely help you get there and you’ll be able to pay off the high cost of tuition with your future earnings. In this way, bootcamps are like an investment in yourself. 

With all investments, there are risks. Some risks involved in paying for a bootcamp are:

 

 1) The risk that you will discover that you do not like data science after all and no longer want to pursue this career path.

2) The risk that you will have trouble finding a data science job after completing the bootcamp.

 

The good news is that most programs offer safety features to help guard against these risks. If you’re worried about risk #1 above, look for a data science bootcamp that offers free or low-cost intro programs. These mini-bootcamps often take just a few days to complete and are a great way to dip your toe in and learn enough about the field to decide whether you want to pursue it further with a bootcamp. If the bootcamp you’re most interested in does not offer a pre-bootcamp option, you can always do your own research by watching videos on YouTube, browsing free resources online, or talking with people you know in the industry. If you don’t know anyone who works in data science, be sure to read our interview with a data scientist to get inside information from someone in the industry!

If you’re worried about risk #2, finding a job, many bootcamps soften this risk with a “pay after you’re employed” policy. This means that, on the off-chance that you cannot secure a data science job, you would not be required to pay tuition. While not all bootcamps have this policy, many do provide robust career resources to make sure you do not end up jobless after completing a bootcamp. It’s a good look for bootcamp companies when their graduates go on to successful careers, so they also have a big incentive to make sure you become happily employed!

 

Why Take a Data Science Bootcamp?

A bootcamp is a great way to break into the field of data science when you don’t have any prior experience. You’ll learn relevant technical skills used by data scientists such as Python, SQL, Matplotlib, statistics, modeling, and forecasting. Many programs have a close relationship with companies that employ data scientists and leverage this relationship to stay up-to-date on the data skills that are needed in the industry.

Most data science bootcamps include hands-on projects in the curriculum and allow students to practice skills on datasets pulled from real-world scenarios. These projects give students a good background to prepare for similar work they might be asked to do in a technical interview and day-to-day in their future jobs.

Apart from learning hard technical skills, bootcamps help prepare students for a successful career by coaching them on soft skills and helping them in their job search. Many bootcamps offer interview practice, resume review, and presentation coaching. Some remain support for students in their job hunt after the bootcamp ends and until students are matched with an employer.

The great thing about entering the data science job market is that so many different industries are in need of data scientists. You may hear all kinds of businesses and organizations talk about their “data-driven” approach. More and more organizations are finding value in collecting, analyzing and storing large amounts of data. To do this on a large scale, they need to employ data scientists. This means that data scientists have no shortage of jobs to apply to and can often have a variety of choices in which industry they join.

Glassdoor lists a variety of industries where data scientists are needed. These include tech companies, government agencies, healthcare, research, and more!

Data Flair, a course provider, laid out six diverse applications of data science. Each of these is a direction you could steer your career in after completing a bootcamp. The six applications of data science are:

  1. Manufacturing – Companies in the manufacturing sector can use data science to inform their business operations and identify inefficiencies. They can collect data on profits, costs, timings, customer reviews, and shipments and then use data science to find trends, identify problems, and make forecasts about future demand.
  2. Banking – Banks work with huge amounts of data in order to keep records and make financial decisions. Data science allows banks to store and query data about every customer’s bank account as well as make predictions and do a risk analysis to inform decisions.
  3. Finance – Similarly to banking, the finance industry also uses data science to inform financial decision-making. Data scientists in finance may use machine learning algorithms with large quantities of historical and current financial data to identify risks and opportunities.
  4. Healthcare – Data in healthcare is immensely useful in medical research, patient service, and diagnosis. Predictive models can be used to evaluate individual patients’ risk factors for diseases and to help doctors make diagnoses. Analysis of large quantities of patient data is vital in medical research and in the development of new treatments. Like any kind of large organization that serves hundreds each day, hospitals manage and query large amounts of data to keep track of patients, supplies, appointments and other operations.
  5. Transport – Transportation on a large scale involves many moving parts – trip durations, demand, fuel prices, navigation, etc. Firms in the transportation sector can use data science to make forecasts, determine routes, and optimize operations. For example, public transit can use data about passenger activities to optimize the areas they serve, how often they operate, and the price of a ticket. Rideshare apps like Uber can use customer and driver data to set fares and evaluate their user experience. Airlines need to use worldwide economic data to make forecasts about fuel prices and to decide how often flights should operate between any two destinations.
  6. E-commerce – While data is useful for any kind of commercial retailer, e-commerce is particularly well positioned to leverage data about supply, demand, customer profiles, and products because so much data can be captured online. In-store commerce is harder to analyze because any data collection must be done manually. For example, a sales clerk could observe how many customers gravitate toward a particular aisle and record their observations to analyze. Online, it’s much easier to capture data about which products customers are interested in and use machine learning to suggest similar products for them.

With so many directions to take a data science career in and so many jobs available, a data science bootcamp puts students in a great position to kick off a new career or transition to their current one.

 

Which Data Science Bootcamp is Right for You?

In addition to considering location, cost and time commitment, here are a few other differentiating factors to consider when aligning your digital marketing bootcamp with your career goals. If you know you’ll need a good deal of support and want robust career services, look for a bootcamp with 1:1 meetings included. On the flip side, if you’re an independent learner, some of the options with less 1:1 support are also less expensive and give you access to high-quality learning materials without extra frills.

For any bootcamp, look out for programs that offer ways to connect with alumni and/or detailed and verified student outcome data (think completion and hiring rates). Since these programs are not federally accredited, it is best to collect as much information as possible before making a financial commitment.

 Ask yourself which of these factors are most important for your desired outcomes: 

  • Relevant curriculum, with scenarios and industry tools you might encounter in the workplace
  • Instructor-led classes, or if you desire, the ability to view class content on demand
  • Real-world projects applicable that can be repurposed for resumes and interviews
  • Feedback from program alumni and ability to network with past participants
  • Partnerships with potential employers and industry veterans

 

Do Data Science Bootcamps Offer Career Services?

Bootcamp programs are generally designed for those without prior industry experience. For this reason, almost all programs offer career services on top of their skills-based curriculum. This might include resume and portfolio review, mock interviews and networking opportunities. Look out for providers that match their students with 1:1 career mentors that offer regular meetings throughout and following program completion. Overall a data science bootcamp can help you initiate a career with very few prerequisites.

 

Data Science Bootcamps vs. Master’s Degrees

Students can develop their data science skills with an advanced degree or with an intensive bootcamp program. While having a Master’s Degree in Data Science can help you land higher-paying positions faster, there are still many reasons to consider a data science bootcamp: 

  • Cost: While some bootcamp tuitions are pricey, a Master’s Degree in Data Science is costly as well. Masters programs can take 2 to 6 years with yearly tuition usually ranging between $10,000 and $30,000.  While bootcamp tuition ranges from $500 to $30,000 for a full program. Masters programs can range from $10,000 to over $100,000!
  • Requirements: There are fewer requirements for applying to online data science bootcamps. Some master’s programs require GRE scores or GMAT scores. Also, for a master’s degree, you first must have a bachelor’s degree. The majority of online data science bootcamps do not require a bachelor’s degree.
  • Time: Since most online data science bootcamps are 10 to 36 weeks, bootcamps can get you into the data science field faster than a master’s degree could. Bootcamps are intense for a short period of time and designed to prepare students with the skills they need to enter a field in data science.
  • Employment: Many data science bootcamps guarantee employment in the field before paying tuition. While a master’s in data science might make students eligible for more advanced roles, bootcamp students can also reach an advanced level by first gaining experience in a more entry-level job.
  • Applicable skills: Compared to a master’s degree program, bootcamps generally put less emphasis on theory and spend more time on hands-on practical learning. 
  • Community: Bootcamps often offer networking opportunities, one-on-one mentors and more to help students enter the data science workforce. Masters programs also are likely to involve teamwork and interaction with industry professionals.

 

 BootcampMaster’s DegreePhD
Time to complete10-36 Weeks2-6 Years4-8 Years
CostLess than $1,000 to $30,000+$10,000 or more per year$20,000 or more per year
SkillsFocus on technical skills and hands-on projectsCombination of applied skills and theoryFocus on data science theory and advanced research.
CommunityCollaboration is often emphasized. Networking opportunities and one-on-one mentors for support are often included.Research projects require collaboration and teamwork.Theses may allow for collaboration.

 

Towards Data Science compared bootcamps and master’s degrees, along with Massive Online Open Courses (or MOOCs), and made observations about each educational path’s outcomes. While master’s degrees and bootcamps are equally successful in placing students in jobs, bootcamps get students there much faster. Online open courses, in contrast, are not as successful at placing students in jobs and may take much longer for students to get through.

 

What Types of Salary Can You Expect After Completing a Data Science Bootcamp?

Completing a Data Science bootcamp is an excellent way to kickstart a lucrative and fulfilling tech industry career! The U.S. Bureau of Labor and Statistics specifically ranked Data Scientists among the top 20 fastest growing professions and Glassdoor even named data scientists the 2nd Best Job in America for 2021! 

Below we’ve listed out average salaries from Indeed for a number of different positions in Data Science, although figures can vary widely by city and level of specialization. Demand for these roles is increasing across the board, so many roles offer additional bonus compensation or other perks.

PositionAverage U.S. Salary
Data Scientist$115,863
Data Analyst$65,998
Database Administrator$88,156
Cloud Architect$134,301
Software Engineer$112,623
Network Analyst$67,896

 

We’ve compiled a list of top data science bootcamps in the U.S. Browse the list below to find a bootcamp that fits your needs and schedule: