Data analytics bootcamps cater to a diverse range of learners, from beginners to career switchers, and even current professionals looking to enhance their skills, providing a versatile gateway into the dynamic world of data analysis.
Some bootcamps might focus more on beginning concepts, while others might be more beneficial for those seeking to upgrade their skills.
It’s important to review the curriculum of a bootcamp before enrolling to ensure that it’s offering the right level of studies for your particular situation.
But what about those who, for whatever reason, cannot or will not pursue a four-year or graduate degree in data analytics?
This is where data analytics bootcamps come in.
Bootcamps are relatively short training opportunities. You can quickly learn coding, software development, and data analytics (or data science) skills through hands-on projects and interactive learning sessions.
In as little as 12-24 weeks, students can learn the basics and advanced details about big data, data analysis, programming, web visualization, etc.
Over the past decade or so, career bootcamps have become increasingly popular, mainly in the business and technological fields. How popular? Despite their lack of accreditation and depth compared to degree programs, bootcamps have grown tenfold since 2013; currently, there are over 200 bootcamps in existence.
Some note their “speed and accessibility” as reasons for their popularity, as some wish to pursue high-paying tech jobs as quickly as possible.
There is also the fact that a data analytics bootcamp costs far less than a four-year degree program. In a compressed curriculum, too, there is less time to study theoretical concepts and more attention to specific technological tools and processes that can be applied immediately in a professional setting.
The admissions process for a data analytics bootcamp is easy. It typically involves filling out an online program interest form, completing an admissions phone interview, and taking a short multiple-choice assessment to measure critical thinking and problem-solving abilities.
Curriculum for a Data Analytics Bootcamp
Fundamental programming, data formatting, and web visualization are among the main topics you could expect to study as a student of a data analytics bootcamp.
With a heavy focus on these subjects, some programs require aspiring students to have a background or take classes in Windows, computer basics, statistics, and programming. Some online programs might have technical requirements, such as a specific operating system or processor.
Below is an outline of a common curriculum seen in data analytics bootcamps:
- Pivot Tables
- VBA Scripting
- Python 3
- API Interactions
- Extract, Transform, Load (ETL)
Front End Web Visualization
- Geomapping with Leaflet.js
Business Intelligence Software
- R Programming
- Big Data Analytics with Hadoop
- Supervised Machine Learning
- Unsupervised Machine Learning
- Deep Learning
Data analytics bootcamps are usually structured around modules, with introductory topics covered in early modules and topics becoming more advanced in later modules.
In many cases, a data analytics bootcamp will start with an introductory course that usually lasts 30 hours and covers computing basics, data life cycle, datasets, and career paths.
Core concepts you are likely to concentrate on in the curriculum of a data analytics bootcamp are data formats, data storytelling, visual communications, artificial intelligence, advanced programming, data wrangling, and data integration.
Other concepts that might be taught in a data analytics bootcamp include statistics and probability, research design, and presentation and communication methods. Classes, virtual or in-person, typically incorporate hands-on assignments, such as building structured code, developing ETL scripts, and creating analytics models.
Final projects could be open-ended and involve building data sets, completing a statistical analysis, or developing a machine learning model.
Examples of actual projects completed in data analytics bootcamps are:
- Smarter Pricing for Airbnb Using Machine Learning
- Building a Vocal Emotion Sensor with Deep Learning
- Predicting Stock Performance from Quarterly Earnings Conference Calls
- How to Build a Voting Recommendation Engine using Twitter Profiles
In all examples, students collected and analyzed data, created and tested models, and drew up detailed solutions, much as data analysts and other data analysis professionals would do in a real-life setting.
Some camps like the one offered by BrainStation provide hands-on learning opportunities in group projects, wherein you will work with other students to build solutions for real-world business issues. Companies such as Microsoft and Google have presented real business cases for these experiences in the past.
Full-time attendance often requires possible long hours—up to 10 hours per day, five days a week. These hours are consumed with coursework, coding practice, and collaborative projects. Programs typically last 12-full-time or 24-part-time weeks regardless of format; some data analytics bootcamps are 26 weeks.
Online Data Analytics Bootcamps
Many data analytics bootcamps are offered online, allowing for flexibility in accessing live interactive classes and working on projects.
Many of these bootcamps are hosted by well-known, recognizable colleges and universities, with some being taught by the same faculty that teach related courses at the hosting institution.
Some are offered through an institution’s continuing education or professional education departments, while others are powered by other sources, such as Fullstack Academy, which focuses on bootcamp education.
While an online data analytics bootcamp might offer more flexibility than in-person camps, there is little or no difference in curriculum, projects, or assignments. Costs between online and in-person can vary, as can class sizes and even prerequisites.
How Much Does a Data Analytics Bootcamp Cost?
While typical financial aid avenues such as grants and federal student loans do not apply to bootcamps, most institutions offer payment plan options. Payment plans can be interest-free. Some institutions might offer a discount for early registration.
Still, other institutions might have scholarship opportunities; for instance, George Washington University in Washington, D.C., offers a $500 scholarship to GWU alumni enrolling in a data analytics or other type of bootcamp.
Attending a data analytics bootcamp part-time could provide the opportunity to work while pursuing your studies, allowing you to earn an income to help pay tuition costs.
Scholarships are available for data analytics bootcamps in some instances; some might offer scholarships, for example, for military members or vets, women in technology, recent college graduates, or entrepreneurs. Deferred tuitions plans are yet another option offered by some bootcamp providers.
Are you guaranteed a job once you’ve completed a data analytics bootcamp? Depending on which camp you’ve attended, the answer is yes!
Some bootcamps might guarantee that you land a job as a data analyst or similar position within a specific amount of time following graduation (such as 180 days for the CareerFoundry bootcamp, which also has tailored coaching with a career services team).
Like the Thinkful data analytics bootcamp, others include personalized career coaching services with unlimited interview practices, resume writing support, and exclusive access to open roles.
Those that offer a money-back job guarantee usually employ a career support staff that is heavily involved in helping students network, find companies and positions that match career goals, and land job interviews.
They might even offer Income Share Agreements (ISAs), wherein students start paying bootcamp tuition only after securing a job in the field.
Still, other bootcamp providers, including General Assembly and BrainStation, do not offer any job guarantees but do have professional support services. General Assembly provides a dedicated career coach, mock interviews, networking opportunities, hiring sessions, and guest panels featuring data professionals.
At the same time, BrainStation hosts a Demo Day that allows you to showcase your final project to hiring managers, data analysis professionals, and others.
Post-Bootcamp Career Paths
You’ve completed a data analytics bootcamp! Now what?
Perhaps the most popular career option following the successful completion of a data analytics bootcamp is that of a data scientist.
These professionals analyze gathered data to find patterns and relations that help answer complex questions for corporations, government agencies, and other organizations.
Information collected and analyzed by data scientists could, for instance, provide solutions in areas of finance, business planning, production, staffing, and marketing.
Indeed.com reports the average annual salary for data scientists is $124,867.
Other possible career paths for those who develop skills in a data analytics bootcamp include:
- Data architect: designs and models data management systems; average annual salary, $131,027
- Data analyst: manipulates large data sets to help inform business decisions; average annual salary, $66,444
- Data engineer: converts raw data into information that data scientists can more easily analyze; average annual salary, $126,065
- Statistician: develops statistical models for data analysis; average annual salary, $97,956
- Business intelligence specialist, or analyst: oversees the collection of information and data to assist businesses in decision-making processes; average annual salary, $69,035
- Machine learning engineer: designs software and algorithms to create predictive models; average annual salary, $160,586
- Software engineer: uses programming languages covered in a data analytics bootcamp, such as Python, to design, install, implement, and maintain software systems; average annual salary, $117,968
You could also apply your data analysis skills to specific areas of business. You might, for example, become a marketing analyst; in this role, you would study collected data focusing on consumer behavior, market trends, and competitor practices to help companies make decisions on new product development and pricing.
The average base salary for a marketing analyst is $60,371. Or, as a financial analyst, you could analyze data regarding investment vehicles, gross and net margins, and growth rates to assist company leaders in making decisions that could lead to increased profits and higher returns. Recently, financial analysts earned a median annual salary of $81,730.
In the end, the intense learning style in bootcamps might not be for everyone, and there is certainly nothing wrong with pursuing a conventional degree in the field of data analytics or data science. But for those seeking flexibility, practical studies over theoretical emphases, and hands-on learning opportunities, a data analytics bootcamp makes a lot of sense.
Frequently Asked Questions
A data analytics bootcamp is an intensive, short-term training program designed to equip learners with essential data analytics skills. These programs focus on practical, hands-on learning and are often geared towards career transitioners or those looking to upskill quickly.
Bootcamps typically cover data collection and cleaning, statistical analysis, data visualization, and use of key tools like Python, R, SQL, Excel, and Tableau.
Most bootcamps last between 3 to 6 months, depending on the program’s intensity and whether it’s full-time or part-time.
Students often work on real-world projects that involve data cleaning, analysis, and visualization, simulating real data challenges in business and industry.
Bootcamps are shorter, more intensive, and focus on practical skills, whereas traditional degrees offer a broader education over a longer period.
Look for programs with experienced instructors, a robust curriculum, hands-on projects, and positive reviews or outcomes from alumni.