Data Science Bootcamp: Become a Data Scientist. Job Guaranteed.

Build data science and machine learning skills on your schedule with our flexible, remote program. Graduate in just 6 months and land a job with 1-on-1 support at every step. If you don't land a job, you'll get a full refund.

In partnership with

Our graduates have been hired by top tech companies

A data science bootcamp on your schedule, backed by our Job Guarantee

Launch your data science career in just 6 months part-time. Our flexible, human-guided curriculum featuring advanced specialization, means you can learn when you want, with support as you need it.

Real human support at every step

Work 1-on-1 with an expert mentor, industry career coach and student advisor when you need guidance from course start to new job.

Hands-on experience

Build job-ready skills with 14 mini-projects, multiple capstones and an advanced specialization project that suits your career goals.

Springboard Job Guarantee

We believe in you and our program, so if you don't land a data science job within 6 months of graduating, we'll give you a full refund.

An industry-leading program

Enrolling with Springboard guarantees you a quality learning experience.
Data Science
Data Science
All categories

What you'll learn in this data science bootcamp

We partnered with industry insiders, so you can learn the skills that employers look for. The 500+ hour curriculum features a combination of videos, articles, hands-on projects, and career-related coursework.

The Python Data Science Stack
Data Wrangling
The Data Story
Statistical Inference
Machine Learning
Software Engineering for Data Science
Data Science at Scale
Advanced Machine Learning
Estimated time: 21+ Hours

Python has become a lingua franca of data science. In this unit, you'll learn to program in Python, how to follow best coding practices, and start using an ecosystem of powerful Python-based tools.

  • Learn how to use Python and its standard libraries
  • Build visualizations with Matplotlib and Seaborn
  • Write clear, elegant, readable code in Python using the PEP8 standard
Estimated time: 54+ Hours

Data scientists spend a lot of time on data wrangling (i.e., acquiring raw data, cleaning it, and getting it into a format amenable for analysis), usually with the help of semi-automated tools. In this unit, you'll learn the most common tools and workflows in Python that simplify and automate this complicated process.

  • Use Pandas to wrangle and clean data
  • Work with different file formats, from plain text, to CSV, to JSON
  • Get an overview of relational and non-relational databases and gain SQL skills
  • Collect data by using Application Programming Interfaces (APIs)
Estimated time: 30+ Hours

Data science is not just about the math, the algorithms, and the analysis. It's also about telling a good story. In real life, data scientists don't work in a vacuum—there's always a client, internal or external, waiting to act based on the results of their work.

In this unit, you’ll practice the concepts you've learned so far by creating a story out of a data set. You’ll come up with interesting questions you can ask of your data set and use plotting techniques to reveal insights you can use to create a narrative.

Estimated time: 46+ Hours

Statistics is the mathematical foundation of data science. Inferential statistics helps data scientists identify trends and characteristics of a data set. Not only are these techniques useful for exploring data and telling a good story, but they pave the way for deeper analysis and predictive modeling.

  • Master the basics of inferential statistics and parameter estimation
  • Use hypothesis testing to determine if a phenomenon is statistically significant
  • Learn how correlation and regression can help identify useful features
  • Build A/B split tests
  • Conduct exploratory data analysis
Estimated time: 120+ Hours

Machine learning (ML) combines aspects of computer science and statistics to extract useful insights from data. It’s what lets us make useful predictions and recommendations, or automatically find groups and categories within complex data sets. In this unit, you’ll learn the major machine learning algorithms (supervised and unsupervised).

  • Use scikit-learn to implement supervised and unsupervised algorithms
  • Learn top ML techniques: linear and logistic regression, naive Bayes classifiers, support vector machines, decision trees, and clustering
  • Review ensemble learning with random forests and gradient boosting
  • Validate and evaluate machine learning systems
Estimated time: 9+ Hours

As a data scientist, no matter how many algorithms you design or how much data you crunch, ultimately you’ll be writing software. Some companies expect their data scientists to contribute directly to the code base, while others have engineers around to help translate prototype code to production.

In this unit, you’ll learn how to be a good citizen of the code base, with a focus on writing better code, testing and debugging, and working with production systems.

Estimated time: 25+ Hours
  • Work with MapReduce, one of the most popular algorithms for large-scale data manipulation
  • Understand NoSQL databases and how they differ from SQL
  • Learn Spark, the industry standard in distributed computing frameworks
  • Learn SparkML and MLlib to implement Machine Learning at scale on Spark
Estimated time: 133+ Hours
  • Recommendation systems, social network analysis, and time-series analysis.
  • Natural Language Processing (NLP): Help teach computers to identify, understand, and interpret human languages.
  • Fundamentals of Deep Learning: Uncover the techniques powering machine translation, self-driving cars, and more.

Request a detailed syllabus

Capstone projects for your portfolio

The best way to learn data science is by working on projects. With Springboard, in addition to small projects designed to reinforce specific technical concepts, you’ll complete two capstone projects focused on realistic data science scenarios that you can show to future employers.
While working on the projects, you'll:
Identify a client’s business problem
Acquire, wrangle, and explore relevant data
Use machine learning to make predictions
Create real-world business impact through data storytelling
Kelly Sims
Graduated 06/2018
Capstone project: Cryptocurrency Price Prediction
David Albrecht
Graduated 08/2018
Capstone project: Capital Bikeshare Rebalancing

Work 1-on-1 with a mentor

Mentor-guided learning not only helps you build skills faster, but also enables career growth.

1-on-1 video calls

Regular guided calls with an experienced data science mentor, where you can ask the questions that matter to you.


Your mentor will help you stay on track and as you tackle your curriculum, project, and career goals.

On-demand mentor calls

Get additional 1-on-1 help from experienced data science mentors within our community, at no extra cost.
"My mentor was great, had real-world experience and served as a great resource to help me define a project as well as solve technical questions with my coding. She also provided extra resources if I wanted to practice or further develop a skill from the program."
Esme Gaisford
Data science graduate, 2018
Ryan Rosario
Data Scientist
Eric Rynerson
Senior Data Scientist
Sameera Poduri
Data Science Manager
Ike Okonkwo
Data Scientist

Swipe to see more mentors

See more mentors

Get the perfect job with 1:1 career coaching

Our career-focused curriculum, 1:1 calls with your career coach, and mock interviews, will help you land your dream job. You can access these and all our career support services for 6 months after completing the program.

Your career coaching calls will help you:
Create a successful job search strategy
Build your data science network
Find the right job titles and companies
Craft a data science resume and LinkedIn profile
Ace the job interview
Negotiate your salary
"Springboard helped with career prep and the job search where we were exploring different companies I'd be interested in. We also did mock interviews and technical interviews.They put me in contact with a few different employers."
Justin Knight
Data science graduate, 2018
Our graduates were hired by...

Our Data Science students launch fulfilling careers

enrolled students in our Data Science Career Track since 2016.
August, 2021
of job qualified individuals who reported an offer, received it within 12 months of graduation.
August, 2021
Average salary increase of Data Science students who provided pre- and post-course salaries.
August, 2021

Is this data science bootcamp right for me?

This bootcamp requires the skills and coding experience listed below. If you don't have any experience, our Foundations to Core program will build your knowledge and help you master Python from scratch, before starting the core curriculum at no cost.


6 months of active coding experience with a general-purpose programming language (e.g., Python, R, Java, C++)
Comfort with basic probability and descriptive statistics, including concepts like mean and median, standard deviation, distributions, and histograms
No data science experience?

Foundations to Core is a beginner-friendly course that will help you master the basics before starting the data science bootcamp at no cost.

Learn more

More questions about the program?

Call or email us to connect with an Admissions Manager who will address your questions and support your journey.

Data science bootcamp start dates

The Data Science Career Track is a 6-month program. Most students devote 15-20 hours a week to complete the course.


Every tuition option comes with Springboard's job guarantee. If you don’t get a data science job within six months of graduation, you get a full refund. Read the full Job Guarantee eligibility terms and conditions here

Scholarship eligibility: Are you a woman or a veteran?
Best value
Pay upfront & save 29% on tuition.
Total tuition before discount
- $4,000
Paid at enrollment
Total cost
Most flexible
Pay for the months you need. Save up to 18%.
$1,890 /mo
Total tuition before discount
- $2,560
Paid at enrollment
Monthly payments during course
Estimated total cost (based upon 6 months)
Enroll now, pay later
Deferred tuition
Fixed cost after you start a job. No percentage of income.
$457 /mo
$13,900 + interest
Total tuition amount (upfront deposit + loan amount)
- Upfront deposit (paid at enrollment)
- Loan amount (max)
Monthly payments during course
Monthly payments after course
$457 for 36 months after starting new job
Estimated total cost after interest
$17,154 (max loan amount $13,200*)
*You can borrow less, but need to pay the tuition difference upfront. Only available for U.S. citizens/permanent residents.
Low monthly payments
Financed tuition loan
Apply for a loan & pay it off in installments.
$69-$214* /mo
$13,900 + interest
Total tuition amount (upfront deposit + loan amount)
- Upfront deposit (paid at enrollment)
$500 - $700*
- Loan amount (max)
$13,200 - $13,400*
Monthly payments during course
$69 - $214* for 6 months (interest payments only)
Monthly payments after course
$422 - $505* for 36 months
Estimated total cost after interest
$16,292 - $20,143*
*Range varies based on approved interest rate. You can borrow less, but need to pay the tuition difference upfront. Only available for U.S. residents.

Meet a few of our alums


George Mendoza

Education: BA, History, Economics
Previous Job: Business Analyst
Current Job: Data Scientist

My mentor Danny Wells was an incredible sounding board while I was learning Python, during my capstone ideations, and throughout their execution. The mock interviews forced me to prepare my pitch and served as a great recap of everything I’d learned up to that point. And I can’t possibly overstate the benefit of doing it all remotely while maintaining a job.


Karen Masterson

Education: Ph.D. in Linguistics
Previous Job: Language IT Specialist
Current Job: Data Analyst

I was searching for a program that I could do online that was both rigorous and intensive, and I found all of that with Springboard’s Data Science Career Track. The program also assigns a mentor that you meet with on a weekly basis, which has been invaluable for the accountability and advice.


Brandon Beidel

Education: BA, Engineering, Economics
Previous Job: Software Developer
Current Job: Data Scientist

Springboard had the four factors that were the most important for me: the ability to learn remotely, the ability to have a flexible schedule so I could still work part-time, dedicated mentors, and Career Services. They did a really good job providing me a structured way to apply for jobs all over the country and ultimately helped me find something that piqued my interest.

Apply for the Data Science Bootcamp

Secure your spot now. Spots are limited, and we accept qualified applicants on a first come, first served basis.


The application is free and takes just 10-15 minutes to complete.

What is included in the course tuition?

500+ hour expert-curated curriculum
Regular video calls with your mentor
Additional on-demand mentor support
Active online student community
Support from community managers
1:1 and group coaching calls
Resume and portfolio reviews
1-on-1 mock interviews
Access to our employer network
100% money-back guarantee

Frequently asked questions

Is this course conducted online, or in person?

All our courses take place entirely online. All you need is an Internet connection.

Are there any prerequisites for this course?

The Data Science Career Track Core course requires a background in probability and statistics and experience in general-purpose programming.

If you don’t have this experience please do apply as you have the option of the Foundations to Core program which teaches you beginner to advanced Python in just 6-8 weeks before starting at no extra cost.

As part of the admissions process, we'll ask you to complete an online technical skills survey. Based on your results, we work with you to determine your ideal starting point. You can read more about Foundations to Core here.

How does the admission process work?

Spots are limited and we accept candidates on a rolling basis. We have a multi-step application process. The first step involves a 10-15 minute questionnaire to learn about your prior educational and work experience. Based on your responses, we might ask for additional information -- e.g. a brief phone interview, or a quick coding and statistics challenge - just to make sure the Data Science Career Track is a good fit for you.

What is the difference between the Data Science, Data Analytics and ML Engineering Career Tracks?

The Data Science Career Track will train you for Data Science or technical Data Analyst roles where you will build machine learning models to predict business outcomes.

The Data Analytics Career Track will train you for Data Analyst roles where you will crunch numbers and generate visualizations using tools like Excel, SQL and Tableau.

The Machine Learning Engineering Career Track will train you for Machine Learning Engineer roles, where you will take a machine learning model and deploy it into production.

To see a more detailed comparison of these programs, head here.