Complete Guide to Data Science Bootcamps in 2022: Online, In-Person and Hybrid

In our new, data-driven landscape, it’s useful for people who work in tech or those looking to switch to a different industry to consider upskilling on their own. Some data science bootcamps can help you fill knowledge gaps, but other programs teach basic fundamentals and build up to advanced topics. Use this guide to compare data science bootcamps and potential careers and salaries, and see if enrolling in a data science bootcamp might be worth it to you.

SPONSORED BOOTCAMPS

Rutgers University

info

Rutgers Data Science Bootcamp

Gain skills needed to analyze data and deliver value to organizations. Complete projects using real data sets from the worlds of finance, healthcare, government, social welfare, and more.

Southern Methodist University

info

SMU Data Science Boot Camp

Develop concrete, in-demand data skills and learn how to help drive business decisions and solve challenges that companies are facing. No programming experience required.

Northwestern University

info

Northwestern Data Science and Visualization Boot Camp

Northwestern Data Science and Visualization Bootcamp teaches practical and technical skills in 24 intensive weeks. Students apply their knowledge to hands-on projects that translate directly into work in the field.

University of Southern California

info

USC Viterbi Data Analytics Boot Camp

Expand your skill set and grow as a data analyst. This program covers the specialized skills to be successful in the field of data in 24 weeks.

info SPONSORED

Frequently Asked Questions About Data Science Bootcamps

What Are Data Science Bootcamps?

Data Science bootcamps are intense educational programs that pack critical data science skills and technologies into a short period of time. They are often intended for beginners, upskillers or career switchers to quickly learn the skills they need to become data analysts or scientists.

How Can I Find a Data Science Bootcamp That Fits My Schedule?

Bootcamps are in-person, online, or a hybrid approach that combines online and campus learning, while others provide an online learning experience. Many schools will work with your schedule or offer part-time programs. Part-time data science bootcamps may take more time to complete, but in some cases, courses are offered in the evening and/or on weekends, which can be very appealing to students with full-time jobs.

Are There Data Science Bootcamps for Advanced Learners?

Yes! Some data science bootcamps are aimed at those with experience in object-oriented programming language, statistics, databases or math. The free Insight Health Data Science: Fellows Program is offered to PhD or MD graduates transitioning to big data jobs at leading healthcare organizations. Other bootcamps offer programs for all skill levels.

Will a Data Science Bootcamp Help Me Get a Job?

If you’re interested in switching to a career in data, a data science bootcamp may help you unlock new opportunities. It is important to assess your current skills and research bootcamp outcomes. Reach out to advisers or recent graduates to see how many students complete the program and land a job within three to six months. You can also check whether or not a bootcamp offers career services such as mock tech interviews or if they have a network of companies that hire their graduates.

Are Data Science Bootcamps Worth it?

Data science bootcamps are a useful way to gain skills in data science quickly compared to earning a four-year degree. Bootcamps focus on marketable skills that may help you land an entry-level data scientist role quickly. However, curriculum, cost, and structure of data science bootcamps are some considerations to think about as you explore your options.

A four-year degree is useful, but typically comes with a higher price tag than a bootcamp. From 2018-2019, the average cost of a four-year degree was $28,123, according to data from the National Center for Education Statistics. Fully immersive online data science bootcamps may cost up to $18,000. Be sure to look into scholarships and other financial aid to help lower your costs. Other bootcamps may offer income-share agreements so there are no upfront costs—you only pay for the program if you land a job in data analytics or data science.

It is also important to consider your career goals along with other factors when assessing bootcamps. Are you interested in becoming a machine learning (ML) engineer? Try searching for bootcamps with instructors with real world experience in machine learning and programs that focus on teaching ML techniques. Ask the admissions teams questions about common career outcomes for their graduates. If they’re mostly working as ML engineers, that program may be worth it.

Another question you may want to ask yourself is how much time can you commit to the program? Some bootcamps offer part-time learning options so students can continue their education while working a full-time job. Even with a part-time bootcamp option, you will likely complete your studies before wrapping up the first year of a four-year degree, allowing you to explore new career options or earn a promotion in your current role.

How to Choose a Data Science Bootcamp

Before you commit to a specific program, consider the bootcamp’s instructor and mentor quality, cohort makeup, curriculum, portfolio work, and outcome rates and support. Data science is skills-based, so you should be looking for instructors who have serious, hands-on experience in your preferred fields. You may want to look for bootcamps that focus on group learning and admit a full cohort of students with diverse backgrounds.

It’s also important to decide how much structure you want. Are you comfortable with self-paced learning? Or do you prefer deadlines, assignments and homework? If you’re new to data science, check out beginner and intermediate levels, which often include lectures and projects in fundamentals such as Python. If you’re looking at advanced fellowships, you’ll have more independence to focus on what you’d like to work on and build your portfolio.

For data science jobs, your portfolio is your real resume: Employers want to know what you’ve done, why you did it and how it’s original. With the ASI Data Fellowship, you have the chance to work with industry partners on real-world problems. A strong bootcamp will help you build a diverse portfolio that’s also geared toward what employers look for in their candidates.

Many boot camps have set themselves up as talent pipelines, funneling trained data scientists to eager partner companies. If you’re hoping to land a job after you graduate, look for programs that provide plenty of career training. For example, some programs set up mock interviews, company site visits and consulting projects. Others provide an in-house career coach and instruction in salary negotiations. You may also want to look for a bootcamp that provides post-graduation support, which sometimes includes alumni networking or emails with relevant jobs for recent graduates.

Most bootcamps advertise job placement rates (some boast rates of 100%), but these percentages are only part of the story. You may only receive job offers from the bootcamp’s partner companies, not end up in a “true” data scientist role, or wait three months before receiving an offer. It’s also possible the starting salary is lower than you expected. Take a careful look at what job placement entails and make sure the career they’re preparing you for is the career you want.

7 Common Steps to Choose a Data Science Bootcamp

1. Establish Your Career Goals

Where do you want to be in five years? Do you want to get a data science job straight out of bootcamp or do you just want a skill set that will allow you to work on independent projects? Knowing your goals will help you narrow your options. If you’re lost in a dead-end data role and not sure what your next step is, you might want to explore the uses of data science in different industries and check out our profiles of data science careers.

2. Contact Data Scientists in Your Chosen Field

LinkedInTwitter, and meet-ups are a great place to start! Ask them what they do during a normal day. Get recommendations on skill sets (e.g., R vs. Python). Talk to them about your education options. You may not need a bootcamp to land a job. A few months with Coursera or other MOOCs and a good textbook could do the trick.

3. Research Requirements in Job Listings

But don’t take them too much to heart. Sometimes, HR departments create a huge list of requirements into the skills section and hope for the best. When in doubt, ask your mentors what knowledge is critical to have.

4. Ruthlessly Assess Your Skill Level

This will help when it comes to deciding whether you need a part-time course in Python, a crash course in Hadoop, or a full three-month immersion in major data science technologies. Think about soft skills too. Do you need practice developing your own projects and public speaking? Do you need some experience leading a team?

5. Contact Bootcamp Graduates for an Honest Opinion

Many bootcamp organizations list their alumni on the website, but you can also do a LinkedIn and Twitter search. Ask for an inside take on coursework, instructors, job preparation and career support after graduation.

6. Create a Budget

That program fee is just the beginning; you’ll also need to think about food, transport, lost wages and accommodation. In a place like San Francisco or New York City, housing can be very expensive. Some bootcamps offer merit, need-based scholarships, and scholarships for women; be sure to ask about options.

7. Draw Up a Shortlist

You can start with our List of Data Science Bootcamps, but you may also want to do your own research. What kind of reputations do the instructors have? Can you commit to full-time work? Some bootcamps are highly selective; what are your realistic chances of getting in?

Graduate Degrees vs. Bootcamps

Let’s say you have a bachelor’s degree in quantitative science (or a related field) and you’re thinking of becoming a data scientist. Perhaps you’ve done a few online courses (e.g., Coursera, Udemy, etc.) and are ready to invest in more education. You may be considering four options: data science bootcamp, a data science bachelor’s degree, a data science master’s, or PhD in data science. Which one do you choose?

We don’t have the definitive answer. Unlike, say, medicine, there is no tried and true path to a career in data science. Some data scientists hold a PhD in statistics and have built up an arsenal of data tools; others have a B.S. and an incredible portfolio of projects. Some entrepreneurs have created startups after minimal time in an academic setting.

BOOTCAMPMASTERSPHD
Typical Time to Complete:
A few hours to three months
Typical Time to Complete:
One and a half to two years
Typical Time to Complete:
Four to seven years
Target Audience:
Aimed at folks who want a data science job after graduation
Target Audience:
Students interested in exploring the field
Target Audience:
True lovers of research and data challenges
Instruction:
Instructors often have industry experience designing real data science solutions
Instruction:
Professors may be a mix of academics with theoretical chops and industry professionals
Instruction:
Thesis supervisors are typically serious academics interested in complex problems
Curriculum:
Coursework is usually focused on applied skills & practical projects
Curriculum:
Coursework typically includes theory as well as applied skills
Curriculum:
Coursework is heavily focused on theory and personal research
Interaction:
Team-based projects and experiential learning
Interaction:
A mix of team-based learning and individual research
Interaction:
Opportunity for teamwork depends on the thesis
Tip:
Focus on mastering key skill sets; gaps in knowledge could be disastrous down the track
Tip:
Amass as much practical experience and job training as possible; the market is typically competitive
Tip:
Be sure your thesis incorporates data analysis, programming, and practical experience

Data Science Jobs

Data science is a broad field with a variety of roles that encompass the skills you may acquire in a data science bootcamp. O*NET OnLine projects job growth of at least 8% for data scientists from 2019 to 2029, higher than the average for all jobs . The median salary for data scientists in 2020 was $98,230 per year. Below are some related job titles:

Data Architect
Data architects develop the framework for data management systems. They create a vision for how data will flow through the business, define standards, and collaborate with multiple stakeholders to translate business specifications into technical solutions.

Data Engineer
Data engineers develop, test and maintain databases, data reservoirs and any other data management systems. They build out pipelines so their organization has easier access to raw data, ensuring optimized retrieval. Some data engineers are more focused on databases and work within data warehouses to develop table schemas.

Data Analyst
Data analysts uncover insights from large datasets to solve business problems. Similar to data scientists, data analysts commonly use programming languages such as R and SQL to retrieve and manipulate data. They also use statistical tools to interpret data and reveal trends.

Business Intelligence Analyst
Business intelligence combines data analytics with business acumen. A business intelligence analyst typically uses data from the company’s past performance to help management make informed decisions. They use a number of tools and techniques to pull data, identify trends and create reports to help guide the company’s strategy.

Quantitative Analyst
Quantitative analysts (quants) develop complex mathematical models that financial companies use to make decisions. Some quants have generalized knowledge, while others are experts in a specific area. Quants may research and analyze market trends to make modeling decisions, test new models, products and analytics programs. They may also collaborate with stakeholders on trading strategies, market dynamics and trading system performance.

Looking for in-person bootcamps? Check out our guides:

Interested in a different career? Check out our other bootcamp guides below:

Data Science Bootcamp Directory

Below is a list of data science bootcamps delivered online, in-person and hybrid.

Last updated: October 2021

This page includes information from O*NET OnLine by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA.

Bit Bootcamp

Data Science & Machine Learning on Big Data

New York, New York

Name of Degree: Data Science & Machine Learning on Big Data

Enrollment Type: Full-Time

Length of Program: 8 weeks

Credits: N/A

Concentrations: N/A

BrainStation

Data Science Bootcamp Online

New York, New York

Name of Degree: Data Science Bootcamp Online

Enrollment Type: Full-Time and Part-Time

Length of Program: N/A

Credits: N/A

Concentrations: N/A

Carnegie Mellon University

Data Science for Social Good Summer Fellowship

Pittsburgh, Pennsylvania

Name of Degree: Data Science for Social Good Summer Fellowship

Enrollment Type: Full-Time

Length of Program: 2 months

Credits: N/A

Concentrations: N/A

CodeOp

Data Science Bootcamp

Barcelona, Spain

Name of Degree: Data Science Bootcamp

Enrollment Type: Full-Time and Part-Time

Length of Program: 6 months

Credits: N/A

Concentrations: N/A

Data Masked Inc.

Product Data Science

Name of Degree: Product Data Science

Enrollment Type: Full-Time and Part-Time

Length of Program: N/A

Credits: N/A

Concentrations: N/A

Data Science Dojo

Data Science Bootcamp

Name of Degree: Data Science Bootcamp

Enrollment Type: Full-Time

Length of Program: Less than 6 months

Credits: N/A

Concentrations: N/A

DataCamp

Data Science with Python

Name of Degree: Data Science with Python

Enrollment Type: Full-Time and Part-Time

Length of Program: Less than 6 months

Credits: N/A

Concentrations: N/A

Dataquest

Data Science in Python

Name of Degree: Data Science in Python

Enrollment Type: Full-Time and Part-Time

Length of Program: Less than 6 months

Credits: N/A

Concentrations: N/A

DS3

Microsoft Research Data Science Summer School

New York, New York

Name of Degree: Microsoft Research Data Science Summer School

Enrollment Type: Full-Time

Length of Program: 1 Month

Credits: N/A

Concentrations: N/A

Admission Requirements:

  • Currently enrolled in an undergraduate program in New York City
Learn more about the Microsoft Research Data Science Summer School from DS3

Data Science Retreat

Data Science Retreat

Berlin, Germany

Name of Degree: Data Science Retreat

Enrollment Type: Full-Time

Length of Program: 3 months

Credits: N/A

Concentrations: N/A

Faculty AI

Faculty Fellowship

London, UK

Name of Degree: Faculty Fellowship

Enrollment Type: Full-Time

Length of Program: 2 months

Credits: N/A

Concentrations: N/A

Admission Requirements:

  • Must have Master’s or PHD
Learn more about the Faculty Fellowship from Faculty AI

Fellowship AI

Machine Learning Fellowship

Name of Degree: Machine Learning Fellowship

Enrollment Type: Full-Time

Length of Program: 3 months

Credits: N/A

Concentrations: N/A

General Assembly

Data Science Immersive

New York, New York

Name of Degree: Data Science Immersive

Enrollment Type: Full-Time

Length of Program: N/A

Credits: N/A

Concentrations: N/A

Admission Requirements:

  • Strong background in mathematics
Learn more about the Data Science Immersive from General Assembly

Insight

Data Science Fellowship

Multiple Locations

Name of Degree: Data Science Fellowship

Enrollment Type: Full-Time

Length of Program: 7 weeks

Credits: N/A

Concentrations: N/A

Metis

Online Data Science Bootcamp

Name of Degree: Online Data Science Bootcamp

Enrollment Type: Part-Time

Length of Program: Less than 6 months

Credits: N/A

Concentrations: N/A

NYC Data Science Academy

Data Science Bootcamp

New York, New York

Name of Degree: Data Science Bootcamp

Enrollment Type: Full-Time and Part-Time

Length of Program: Less than 6 months

Credits: N/A

Concentrations: N/A

Admission Requirements:

  • Master’s degrees or Ph.D.s in Science, Technology, Engineering or Mathematics, or equivalent experience.
  • Bachelor’s or non-STEM degrees will also be considered.
Learn more about the Data Science Bootcamp from NYC Data Science Academy

Springboard

Data Science Bootcamp

Name of Degree: Data Science Bootcamp

Enrollment Type: Part-Time

Length of Program: 6 months

Credits: N/A

Concentrations: N/A

Admission Requirements:

  • 6 months of active coding experience
Learn more about the Data Science Bootcamp from Springboard

The Data Incubator

Data Science Fellowship

Name of Degree: Data Science Fellowship

Enrollment Type: Full-Time and Part-Time

Length of Program: Less than 6 months

Credits: N/A

Concentrations: N/A

Admission Requirements:

  • Master’s degree completed before the program begins
  • PhD degree completed before the program begins
  • PhD degree that will be completed within 3 months of the conclusion of the program
  • Bachelor’s degree and extensive experience in a data-related position
Learn more about the Data Science Fellowship from The Data Incubator

Woz U

Data Science Training Program

Online

Name of Degree: Data Science Training Program

Enrollment Type: Part-Time

Length of Program: Less than 1 year

Credits: N/A

Concentrations: N/A