How to Choose the Best Data Scientist Bootcamp (and Why Join One)

How to Choose the Best Data Scientist Bootcamp (and Why Join One)

Posted by Vivian Zhang

Updated: Sep 30, 2021

With so many providers on the market these days, it can be challenging to pinpoint the best data scientist bootcamp for your needs. And if you are a relative newcomer on the data science scene, you may not even know where to begin. 

This article should help make a better sense of what is becoming an increasingly oversaturated industry. However, before we start our list of the best data science bootcamps in 2021, we will look into why it may be a good idea to join a bootcamp in the first place.

The 5 Best Data Science Bootcamps in 2021

To help you choose a data scientist bootcamp that works best for you, here are our top choices for this year in no particular order. Keep in mind that some on-campus programs may only be available online due to the pandemic.

1. NYC Data Science Academy

Tuition: $17,600 total, with third-party financing options available

Duration: 12 weeks (full-time) or 16-24 weeks (part-time)

Location: In-person, remote, and interactive online learning available

Accredited: Yes! 

Our team has worked incredibly hard to create the best data science bootcamp currently on the market – and the industry experts agree. 

In 2021, both SwitchUp and Course Report, the leading third-party reviewers of the world’s top tech bootcamps and programs, ranked us the Best Data Science Bootcamp for the fifth year running. We are also the only data science bootcamp with accreditation by the Accrediting Commission for Continuing Education & Training (ACCET). 

Our Curriculum

We developed our immersive program with one goal in mind: to prepare you for a career in data science. We want to equip you with the knowledge and tools you will need in real life, so our course combines lectures with real-world data challenges and project-oriented exercises built specifically around the skills employers look for.

The 400-hour Data Science with Machine Learning curriculum has seven modules:

  • Prework: You will learn the foundations of R and Python and revisit the fundamentals of calculus, statistics, and linear algebra.
  • Data Science Toolkit: We will introduce you to common data analysis tools such as SQL and GitHub.
  • Data Analytics with Python: You will learn to work with different data structures and data analytics and visualization packages. At the end of the module, you will use Python code to analyze data, solve concrete problems, and visualize your analyses.
  • Data Analytics with R: This course will teach you to leverage R functions and libraries to load, save, wrangle, analyze, and visualize data using standard statistical techniques.
  • Business Cases in Data Science: In this module, you will practice applying data science methods in real-world business contexts. 
  • Machine Learning: You will learn the foundations of supervised and unsupervised machine learning, build a reproducible pipeline, and explore tree-based models and clustering techniques.
  • Advanced Topics: This module branches off into more advanced topics like scalability, big data, cloud computing, and deep learning. 

Each module includes a theoretical component as well as various projects to enable you to practice your skills. By the end of the bootcamp, you will have completed a minimum of four large-scale, real-world projects to showcase to potential employers. 

Career Services

We will provide you with comprehensive career assistance, including:

  • Resume and LinkedIn profile reviews
  • Technical and behavioral interview training
  • Mock coding challenges
  • One-on-one career coaching
  • Workshops, meetups, and alumni presentations 
  • Lifelong access to our hiring partner network


While we cannot guarantee success, 93% of our students receive an offer for a top data science position within six months of graduation.

2. General Assembly

Tuition: $3,950 to $15,950 up front with flexible financing options available

Duration: 10-12 weeks (part-time), 13-14 weeks (full-time), 24 weeks (immersive)

Location: 15+ in-person and 25+ online communities across the U.S., Europe, Asia, and Australia

Accredited: No😔

With its part-time data science courses starting at just $3,950, General Assembly is one of the more affordable providers on the market. And if your employer agrees to foot the bill, it can cost you $0. If you choose to go with the full-time course, it will cost you $15,950 upfront. You can also pay in installments, apply for a loan, or sign an income share agreement.

The course is for people with programming or quantitative backgrounds and covers the fundamentals of data science:

  • Python programming
  • Exploratory data analysis
  • Classical statistical modeling
  • Machine learning models 

You will also cover more advanced topics and learn to synthesize large data sets and predict patterns using Git, SQL, UNIX, and Python.

As a student, you can also benefit from a dedicated in-house career coach who will help you prepare for interviews, build a portfolio, connect you with hiring managers from General Assembly’s networking community, and more.

3. Insight

Tuition: $24,000 upfront with a full-refund guarantee, $0 down payment with a deferred payments loan, or $0 down payment with a 12% minimum income share agreement 

Duration: 7 weeks (in-person or remote)

Location: Boston, Los Angeles, New York, Seattle, Silicon Valley, and remote

Accredited: No😔

Insight’s fellows program is an immersive seven-week training for post-doctoral students looking to transition from academia to a corporate career in data science. To qualify for this data science bootcamp, a Ph.D. is a must. You also need to have a background in: 

  • Physics & Astrophysics
  • Mathematics & Statistics
  • Neuroscience & Bioinformatics
  • Engineering & Computer Science

Interestingly, there are no classes nor textbooks – you get to learn directly from Insight alumni and industry experts. 

Insight is also one of the few providers that offer a data science bootcamp job guarantee. If you pay the full tuition of $24,000 upfront, you will get a full refund if you do not accept a relevant job offer earning at least $90,000 per year within six months of the end of the program. In addition, you make no monthly payments until you start making over $7,500 per month.  

4. BrainStation

Tuition: $15,000, with flexible financing options and scholarships available

Duration: 12 weeks of live online classes (full or part-time)

Location: London, Miami, New York, Toronto, Vancouver, and remote

The Online Data Science Bootcamp Package is a rigorous, project-based program that builds on your previous education and work experience – so it is not for complete novices. Students can expect to collaborate a lot, but BrainStation maintains a low student-teacher ratio, so there should be sufficient supervision and expert feedback. 

The program focuses on developing outcome-based skills and has a dynamic curriculum that BrainStation updates in real-time. You will use R, Tableau, Python, real-world data, machine learning, and more to create five projects and one big portfolio piece. This should help improve your understanding of statistical methods, modeling techniques, and big data. 

BrainStation also offers a Career Success Program. As a bootcamp student, you will have the chance to connect with industry professionals, career coaches, technical recruiters, educators, and BrainStation alumni. There are opportunities for:

  • Community meetups, workshops, and other industry networking events
  • Help with resumes and applications
  • Tips for building a personal brand and interviewing for jobs
  • General career development advice

At the end of the bootcamp, you will also be able to present your final project to BrainStation’s hiring partners at an online graduate exhibit.

5. Flatiron School

Tuition: $16,900 upfront, 12 interest-free monthly installments, or pay with a loan. Scholarships are also available. 

Duration: 15 weeks (full-time) or 20-60 weeks (self-study)

Location: In-person and online

Accredited: No 😔

Flatiron was the first provider to release third-party-examined job data for its bootcamp students. In 2020, on-campus data science alumni had an employment rate of 84% and an $807,000 starting salary.    

The full-time program comes with an intensive schedule, live lectures, group work, and lots of accountability. If you prefer to learn on your own time, the flexible self-study program has the same curriculum but at a more relaxed pace. You work independently and get to set your schedule, with the option to sign up for study groups or one-on-one sessions with an instructor.

The curriculum covers the fundamentals of:

  • Data analysis and engineering 
  • Scientific computing and quantitative methods
  • Machine learning fundamentals
  • Advanced machine learning

At the end of the course, you will complete an individual, large-scale machine learning and data science project to practice and showcase your skills. 

The tuition includes one-on-one career coaching post-graduation, mock interviews, and access to Flatiron’s employer network and their proprietary job-search framework.

What Alternatives to Data Science Bootcamps Are There? 

Data Science Bootcamps are one of the best ways to learn about data science, but there are other options. There are other mediums you can explore, and none are inherently better or worse than others. For optimal results, mix and match your sources of information based on your:

  • Individual needs and interests
  • Education and career stage
  • Finances
  • Overall life situation
  • How much you already know about data science

So, bootcamps are not your only option. They are just one – albeit essential – option to consider alongside alternatives such as:

Self-Study Resources

You can find a plethora of data science materials online. Many are available for free. These range from books, podcasts, webinars, tutorials, and YouTube videos to entire courses provided by top universities or digital platforms like Khan Academy

Self-study materials are a great way to build upon what you learned from a formal setting or dive deeper into topics that interest you on your own time. You can also use these resources to hone your skills or practice what you find challenging. Self-directed study helps get into the habit of continuous learning, which is a must for data scientists.

If you are a complete beginner, however, you may find self-learning resources confusing and overwhelming. Data science is a broad discipline. Trying to create a curriculum for yourself with little to no knowledge of the subject will likely be unproductive and a waste of your time. 

Credibility-Building Activities 

Do you want to practice your skills, test them out in the real world to see how you stack up against your peers? If so, creating personal projects or participating in Kaggle competitions and open-source contributions is the way to go. 

As a bonus, you may even catch the eye of a potential employer. At the very least, you have a chance to build a portfolio and establish connections in the industry without getting a job first.

Of course, these activities require you to already have some knowledge of data science and experience working with the relevant tools, so these will not be an option if you are still a novice. 

Formal Education 

A formal degree or certification such as a Master’s degree, Ph.D., or a data science fellowship will probably have the highest impact in terms of credibility on the job market. It can also provide you with high-quality, in-depth training. 

On the flip side, however, these degrees often require considerable investment money, costing individuals thousands of dollars per year.  In addition, formal education will also be an investment of time. This may be challenging if you have a full-time job, family commitments, or a debt to pay off. 

Furthermore, data science fellowships may require you to have relevant work experience and a Master’s degree or Ph.D. in a related field. Therefore, if you are just starting your career in data science, you may not be eligible to apply. 

Why Bootcamps Are the Best Option to Learn Data Science

For a successful career in data science, you need two things: in-depth knowledge and credibility. Bootcamps give you the best of both worlds. They combine well-structured, relevant, accessible, and vetted information with certification by accredited organizations. 

Better still, data science bootcamps are generally more affordable and less time-consuming than a full-fledged Master’s degree or Ph.D. You also get instant access to a community of like-minded professionals from day one. 

Data Science Bootcamps FAQs 

Can You Become a Data Scientist from a Bootcamp?

A bootcamp is one of the most effective ways to get your foot in the door. NYC Data Science Academy gives you the high-quality training and industry connections you need to start your journey. However, a career in data science requires lifelong learning, so be prepared to do a lot of self-study and attend various continuing education programs. 

Are Data Science Bootcamps Worth It to Get a Data Science Job?

Bootcamps are becoming increasingly valued by employers. As long as you invest in a course by a credible provider (and put in the work), a data science bootcamp can give you a real competitive edge. 

What Are the Best Data Science Courses of 2021?

Which course will work best for you will depend on your individual needs and preferences, but trustworthy third-party reviewers like SwitchUp and Course Report are always an excellent place to start your research. 

You can also try looking up search terms like “best data science bootcamp with job guarantee,” “best data engineering bootcamp,” or “best data science bootcamp” on Reddit and other public forums, but be sure to take unverified anonymous reviews with a pinch of salt.

How Long Is a Data Science Bootcamp? 

The duration varies between providers, but 10-12 weeks is standard for a full-time course. 

Join the Best Data Scientist Bootcamp for the Fifth Year Running

Together, we can take your data science career to the next level. 

Apply for a bootcamp with NYC Data Science Academy today to start growing your career.

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Vivian Zhang

Vivian is the CTO and School Director of NYC Data Science Academy and CTO of SupStat. With her extensive experience working in the data science field, she developed expertise in multiple programming languages, including R, Python, Hadoop, and Spark. In August 2016, Forbes ranked her amongst one of the nine women leading the pack in data analytics. In 2013, she created the NYC Open Data Meetup group, which stands as one of the largest data science communities offering meetups, conferences, and a weekly newsletter. In her spare time, Vivian enjoys meeting people and sharing her motivational stories with our students and other professionals

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