Right now with help wanted signs appearing everywhere, it seems as though every job is in high demand. But even in this climate the demand for data scientists—people who process and analyze massive amounts of data to help companies glean valuable insights—is astounding. One measure of that: The U.S. Bureau of Labor Statistics projects a 22% increase in demand for trained data scientists by 2030.
Given the unprecedented demand, it’s only natural that many people are aspiring to a successful career in the profession. But is it really for you? To get a sense of what it takes to be a data scientist, consider enrolling in a data science bootcamp, a training program where you can learn which skills employers value. Here I've summarized seven of the best bootcamps, including what each covers, prerequisites, and what each costs.
These immersive and intensive programs teach participants the fundamentals of data science to help them prepare for entry-level jobs in the industry. Running anywhere from three to six months, data science bootcamps are shorter than traditional two- and four-year degree programs and provide more opportunities for hands-on learning.
Data science bootcamps include a wide variety of topics designed to teach students different languages and frameworks, including a basic introduction to data; practical knowledge of languages such as SQL, R, Hadoop, and Python; and an overview of machine learning, A/B testing, statistics, and related topics.
Over the course of their studies, students learn about data science programming, data analysis, data visualization, and the math skills they need to begin careers in data science. Bootcamp graduates know how to discover patterns in data to make predictions that help their organizations make better decisions. Even if you don't end up becoming a data scientist, you'll end up with a better understanding of what the job entails, what you can expect from data scientists you may work with, and how top put requests into terms a data scientist will understand.
In addition to establishing a solid foundation in data science, bootcamps offer networking opportunities, the latest curricula, and in some cases career coaching beyond anything offered at four-year institutions. The best bootcamps adjust their content frequently to ensure that students are learning about the most relevant and up-to-date industry trends.
Whether you attend an in-person or virtual bootcamp, you can still build your professional network. Bootcamps offer students opportunities to connect with experts and speakers in the field of data science as well as form connections with classmates and study groups.
Building a professional network not only provides an opportunity to see where you might want to go with data science, but it also can help you find a job as a data scientist upon graduation.
Most data science bootcamps, whether virtual or in-person, offer one-on-one support from instructors and lecturers for students who need extra help. Many bootcamps ensure that you have the same instructor throughout your learning experience, in contrast to a university where your professors change from class to class.
Unlike the professors at a college or university, who remain in academia to study their chosen fields and may be more interested in academic research than in teaching the basics, bootcamp instructors often are hired because of their successful experience working in data science in the real world. Some bootcamp instructors even hire data science managers or team leaders in the industry, which means they know exactly what you need to learn to get a job in the field.
Over the course of your time at a bootcamp, instructors will make assignments and design projects intended to help you build a portfolio of work.
These bootcamps tend to cost less than degree programs, but they're not cheap: Prices vary widely, from $10,000 to almost $30,000. Bootcamps typically offer several financing options, including monthly payment plans, as well as scholarships. Some employers may cover the cost of tuition, so be sure to ask.
The average salary for a data scientist is $134,000, but starting salaries can be over $150,000, and as you improve your skills and experience, you can expect that number to increase.
We selected seven well-known data science bootcamps and asked the sponsors to tell us about their programs to help you determine which might best suit you. While we can get you pointed in the right direction, you should do your own research and reach out to bootcamp representatives before making your decision. Here's a summary of each program.
Calling itself a “career transformation experience,” BrainStation offers a full-time, 12-week data science bootcamp with part-time options in data science, data analytics, and Python.
The full-time program begins with two weeks of learning online to ground students in the foundational data skills they’ll need to succeed in the program. After the online segment concludes, students participate in 10 weeks of on-campus, project-based learning, which emphasizes collaboration and outcome-based skills development.
BrainStation, which offered its first bootcamp in 2012, operates in five locations: Toronto and Vancouver in Canada, New York and Miami in the United States, and London in the United Kingdom. COVID-19 restrictions mean that some courses may be held online. With a teacher-to-student ratio of 1:8, students have ample access to faculty as well as to a wide variety of additional training resources and materials online.
The program is divided into five units: fundamentals of data analysis and visualization, analysis for data science, machine learning techniques, big data fundamentals with machine learning, and professional development.
Instruction primarily focuses on SQL and Python and on several packages and libraries created for statistical analysis and data science such as NumPy, Pandas, Matplotlib, and Scikit Learn. The program emphasizes modeling and ML techniques using Python, but students are also exposed to tools such as R and Tableau, along with big data tools such as TensorFlow, Hadoop, and Spark.
Students work on a real-world business case prior to graduation to gain practical, hands-on data science experience. Working alongside industry practitioners, students collaborate with teams from other BrainStation bootcamps. Students’ projects are showcased at a graduation Demo Day, attended by hundreds of hiring managers, data professionals, and BrainStation alumni.
While a bachelor’s degree in science, technology, engineering, or math is considered “beneficial,” it isn’t required. Full-time students are in class 35 to 40 hours per week throughout the 12-week program, but additional time is required outside of class to complete projects. Part-time students attend classes on Tuesday and Thursday evenings and all day on Saturdays.
The bootcamp offers a range of career services, including portfolio development, mock interviews with current industry professionals, resume and job search workshops, and office tours of leading tech companies.
Cost: A one-time payment of $15,000 or 24 monthly payments starting at $664. Scholarships are available.
This bootcamp requires a foundation in basic Python skills, so it starts off with a free beginner course, Intro to Python. While this bootcamp was previously an in-person program in New York, Byte Academy has moved exclusively to online instruction in response to the pandemic. There are, however, regularly scheduled networking opportunities in New York that are open to current students, alumni, and both current and past staff members.
The 24-week program begins with 10 weeks of intensive instruction, with a teacher-to-student ratio “as low as” 1:5, followed by a 10-week, hands-on experiential project and a four-week mandatory internship with a potential employer.
The bootcamp promises to teach students how to extract meaningful patterns from data, as well as help them learn the applied coding skills needed to turn theory into practice. Students apply their knowledge during a succession of projects and project reviews, as well as through the practice of foundational interview concepts designed to build up the quality of students’ code and prepare them for employment.
During the intensive instruction period, students learn the basics of data science, object-oriented programming, data structures, and software theory, as well as machine learning theory, supervised and unsupervised learning, and neural networks. Python is the core coding language; the program also covers libraries such as Pandas, NumPy, and Matplotlib. Coursework also touches on Jupyter notebooks, some web scraping, SQL, Git protocol, Bash, Linux, and system architecture.
Costs: Byte Academy's tuition is $25,000, with financing options available. But its website highlights a “no tuition until you’ve made it” agreement, which it describes as “enroll now and pay when hired.” Under this option, program graduates earning at least $40,000 annually pay 15% of their salary for three years, up to a maximum of $30,000.
This 16-week online bootcamp offers an optional three-month internship that includes extensive career support afterward. Focusing on data science, engineering, and machine learning, the program—first offered in 2014—is conducted online live for three hours weekly and assigns two to three hours of homework per week. Live sessions are recorded for later review. The teacher-to-student ratio is 1:15, and instructors are available immediately before and after class as well as during weekday office hours.
No prior knowledge of data science or programming is required. During the bootcamp, all students work collaboratively, but submissions are graded individually. In addition to in-class model-building and coding exercises, attendees also spend an average of 15 hours over the course of the program working on a data science competition.
Cloud-based Jupyter Notebooks allow working from anywhere via a browser-based tool rather than having to purchase or work in a dedicated programming environment. Instructors teach using R but also offer the corresponding Python code.
Tools used include Azure, AWS, Hadoop, Spark, and Kaggle. Topics covered include building predictive models, cross-validation techniques, evaluation metrics, A/B testing, linear models, and the end-to-end process of handling data from extraction to real-time analysis.
After the bootcamp, students have access to an extensive repository of tutorials, demos, and exercises to continue developing new skills. Graduates can receive a data science certificate from the University of New Mexico.
Costs: Bootcamp without internship and career support: $2,999; bootcamp with three-month practicum internship, mentoring, development of a data science portfolio, and career support: $9,999. Financing options are available, including payment plans, interest-free loans, and deferred payments until graduation.
This 20-week online bootcamp is centered on five intensive projects that require a weekly time commitment of 15 to 20 hours; before the program begins, students complete 60 hours of online pre-work. Students are expected to have experience in both programming and math. While a deeper background in either area is helpful, it isn’t considered critical to success.
Metis offers a free admission prep class to build skills in linear algebra, calculus, probability, statistics, and Python fundamentals.
The bootcamp focuses on five modules: exploratory data analysis, linear regression and web scraping, business fundamentals for data practitioners, machine learning classification, and natural language processing and unsupervised learning.
Following each module, students demonstrate mastery of the subjects by completing a business-oriented project designed to help them develop a portfolio of work to share with prospective employers. Languages, systems, and tools covered include Python, Jupyter Notebooks, Git and GitHub, NumPy, SciPy, Pandas, Statsmodels, Sci-Kit Learn, Keras, Spark, Google Cloud Platform, AWS, SQLite, MongoDB, Tableau, Matplotlib, Seaborn, HTML, CSS, BeautifulSoup, Selenium, Flask, and Heroku.
For each project, students learn to identify business problems as well as extract, clean, analyze, and interpret data before communicating the results in a presentation. The program focuses on the full lifecycle of being a data professional, in addition to teaching theory and technologies.
Metis combines asynchronous learning with weekly live online interaction. Students watch on-demand lectures, complete online exercises and assessments, and engage with instructors, teaching assistants, and classmates via Slack and during Zoom office hours—including weekly half-hour, one-on-one sessions with an instructor.
After graduation, students have access to all course materials for six months and career support until hired.
Cost: $11,000; $3,000 scholarships are available for women, the LGBTQ community, members of underrepresented groups, and U.S. military veterans. Installment plans are available, including zero-interest payment plans for qualified applicants. Loans are also available.
This 400-hour bootcamp teaches data science with machine learning; it can be completed over the course of 12 weeks as a full-time, hybrid in-person/remote program at the academy’s New York facility. Students may also choose to participate through distance learning—16 weeks for a full 40 hours per week or 24 weeks for a 20-to-30-hour part-time program.
Applicants for the highly competitive program, which began in 2015, must hold at least a bachelor’s degree, with a strong preference for prospective students with degrees in STEM disciplines and those who already hold a master’s degree or doctorate. Applicants with strong domain knowledge in an area that employs data scientists and who have some background in either coding or statistics also will be considered.
In rare circumstances, applicants without a degree may be considered, but they must be high school graduates who can prove exceptional talent in computer programming, have proof of domain knowledge in math and science, have two letters of recommendation from relevant professionals, and be able to pass the academy’s technical assessment with a grade of B or better.
Students take seven modules to learn the major tools and methods for performing data analyses and apply them to various projects typically found in the data science field. Students complete four projects using real-world datasets before completing a capstone project that's usually sponsored by a New York-based company.
Students not only learn the knowledge and skills for data analytics but also study supervised and unsupervised models of machine learning and other more advanced topics.
Before the bootcamp begins, students must complete 40 hours of online coursework and more than 200 exercises to prepare to work with both R and Python as well as revisit basic concepts in linear algebra, calculus, and statistics.
At the foundation level of the program, students learn to employ R and Python for data analytics projects and for presenting research results effectively. Beyond the foundational level, students study machine learning with Python and carry out research projects that involve advanced data science methods and strategies.
The program also exposes students to concepts and practices in deep learning and big data. In addition to R and Python, students learn about Linux, GitHub, SQL, Hadoop, and Spark, among myriad other tools.
Cost: $17,600. Payment plans and scholarships are available.
This unique program—Europe’s largest data science training bootcamp—requires applicants to hold either a master’s or doctorate degree in an analytical field. Offered since 2014, the five full-time weeks of intensive, project-based training are intended to help professionals and academics who already have the foundational skills of a data scientist transition into new careers in the field.
Unlike most data science programs, where the focus is on theoretical learning, S2DS recognizes each student’s prior education and experience and emphasizes training that develops analytical knowledge to tackle a real data science problem with a commercial partner. After a handful of introductory best-practices lectures, the program concentrates on training students to communicate results to non-experts and aligning data analysis with key business drivers.
The online program operates from 9 a.m. to 6 p.m., U.K. time, Mondays through Fridays, and includes optional evening networking events. Students work in five-member teams throughout the bootcamp. Each team works with a program mentor, a technical mentor, and a business mentor. Teams meet with program mentors weekly and with technical mentors daily. Business mentors interact with the team weekly for a minimum of half a day.
The program does not teach coding and does not have a set curriculum. Applicants must have an intermediate level—at least 100 hours—of coding experience in Python or R. Specific tools and technical skills for each project are customized through on-the-job development.
Cost: £800 ($1,043 at the time of writing). Partial scholarships are available.
Acting as an aggregator of online coursework offered by several universities and corporations, Simplilearn coordinates the six-month Caltech Data Science Bootcamp in collaboration with IBM. Designed for working professionals, the program features master classes by distinguished Caltech faculty and IBM experts, with hackathons and “Ask Me Anything” sessions hosted by IBM.
The program, operated under the auspices of Caltech’s Center for Technology and Management Education, covers data science topics such as Python and R programming, machine learning, deep learning, and data visualization tools through an interactive learning model with practical labs and live sessions taught by global practitioners.
Applicants must hold a bachelor’s degree and have prior knowledge of programming and mathematics; preference is given to those with at least five years or more of formal work experience.
Students participate in two live interactions each week and also have access to “learner success managers,” who offer one-on-one mentoring on demand. There are also periodic group mentoring sessions. Among the languages, systems, and tools taught are R, Python, Pandas, NumPy, SciPy, Matplotlib, Seaborn, Bokeh, Dash, Plotly, StatsModels, Nltk, sklearn, TensorFlow (with Keras), Jupyter LAB, Tableau, PowerBI, and R Studio.
Students collaborate on four key projects—mobility as a service, automobile manufacturing, e-commerce, and retail—and there are more than 25 additional hands-on projects from major American corporations available. Among the topics covered during the bootcamp are exploratory data analysis, descriptive statistics, inferential statistics, model building and fine-tuning, supervised and unsupervised learning, ensemble learning, deep learning, and data visualization.
Although the bulk of the program is conducted online, requiring about a 10-hour commitment per week over the course of the bootcamp, there is also an in-person visit to Caltech’s Robotics Lab.
Cost: $8,000. Installment plans and loans are available.