SIX MONTHS • ONLINE • LIVE 1:1 MENTORSHIP • CAREER-FOCUSED

Data Science Bootcamp: Pay only after you get a data science job.

With deferred tuition and a job guarantee, investing in yourself is risk-free.

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Structured to fit into your life, guaranteed to get you a job in data science
Learn at your own pace with 1-on-1 mentorship from industry experts and support from student advisors and career coaches.
Unlimited 1:1 mentor support
Meet weekly with your personal mentor, with as many additional calls as you need.
Hands-on experience
Learn by building 14 real-world projects and developing a data science portfolio.
Career support & job guarantee
Get a data science job within 6 months of graduating or your money back.
What you'll learn in this bootcamp

The curriculum is split into 18 units covering the topics below, with a specialization that aligns with your data science career goals.

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

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The Springboard learning experience

Learn from the best online resources

We work with hiring managers and experts to curate our curriculum.

Get guidance from your mentor

Your mentor will provide constructive feedback and challenge your thinking.

Learn from your peers

Connect with students and alumni who share your career path in our forum.
Develop portfolio-worthy capstone projects
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 1:1 with a mentor
Mentor-guided learning not only helps you build skills faster, but also enables career growth.

1:1 mentorship

Have weekly guided calls with your personal mentor, an industry expert.

Accountability

Your mentor will help you stay on track and as you tackle your goals.

Unlimited mentor calls

Get additional 1:1 help from a mentor from 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 unlimited 1:1 career coaching

Career-focused course material is paired with personal coaching calls to help you land your dream job. You’ll have 6 scheduled calls, with unlimited access to more. And full career support continues for 6 months after completing our bootcamp.

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...

Student outcomes

2,300+
Total students
who have enrolled in the Data Science Career Track since its launch in 2016
3%
Job guarantee refund rate
among 328 eligible students who have completed the 6-month job search period
$25.8k+
Average salary increase
from students who provided pre- and post-course salaries, through July 21, 2020

Is this program right for me?

This data science bootcamp was designed for those with prior experience in statistics and programming, such as software developers, analysts, and finance professionals. All professional and academic backgrounds are welcome.

Prerequisites

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
Need more prep?

If you don't meet these requirements, enroll in our Data Science Career Track Prep course to level up your skills.

Learn more

More questions about the program?

Schedule a call with our Admissions team or email Patricia, our Admissions Manager, who will help you think through the decision.

The admissions process

1
Submit your application
Fill out our application form to get started. There is no application fee. It takes about 10-15 minutes. You should expect a reply in 2-3 business days.
2
Interview with an Admissions Director
We'll discuss your background and learning goals to make sure you're a good fit for the program.
3
Pass the skills survey
If it's a fit, we'll send you a technical skills survey to test your statistics and programming knowledge. Applicants spend up to 3 hours on this.
4
Join the program
If you pass the skills survey, we will send you a registration link. Choose the start date and payment plan that works for you (we can help!). You’ll be one of the fewer than 20% of applicants who secured a spot in the Data Science Career Track!
Fill out our application form to get started. There is no application fee. It takes about 10-15 minutes. You should expect a reply in 2-3 business days.

Data science course start dates

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

Tuition

The full tuition of the program is $8,940. If you pay upfront, you get a 16% discount. Remember, if you don’t get a job within 6 months of completion, you’ll receive a full refund. See job guarantee eligibility terms

Scholarship eligibility: Are you a woman or a veteran?
Upfront discount
Pay upfront and save 16% on tuition
$7,500
$8,940
Paid at the time of enrollment$7,500
Total cost$7,500
Month to month
Pay only for the months you need, up to 6 months
$1,490 /mo
Total: Up to $8,940
Paid at the time of enrollment$1,490
Monthly payments during course$1,490
Total costVariable (up to $8,940)
New
Deferred tuition plan
Pay monthly only after you start a data science job
$655.55 /mo
Total: $12,500
Paid at the time of enrollment$700 refundable deposit
Monthly payments during course$0
Monthly payments after course$655.55 for 18 months after starting new job
Total cost$12,500
* only available for U.S. residents
Climb Credit loan
Finance your education with low monthly payments
$52-104 */mo
Total: $10,160 - $11,523*
Paid at the time of enrollment$500
Monthly payments during course$52 - $104* (interest payments only)
Monthly payments after course$274-$303* for 36 months
Total cost$10,160 - $11,523* (Loan amount of $8,440)
* range varies based on approved interest rate and 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 Career Track

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

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

What is included in the course tuition?

500+ hour expert-curated curriculum
Weekly video calls with your mentor
Unlimited additional 1:1 mentor support
Active online student community
Support from community managers
1:1 career coach calls
Resume and portfolio reviews
1-on-1 mock interviews
Access to our employer network
100% money-back guarantee
Frequently asked questions
What are the eligibility criteria and terms for the job guarantee?

A career transition into data science is exciting, but involves focused and consistent effort. We are thrilled to have your back in this journey and ask for an equal commitment from you. In order to be eligible for this job guarantee, you should:

  • be 18 years or older
  • hold a Bachelor’s degree from any educational institution in any subject, which is still a requirement by most employers for these roles
  • be proficient in spoken and written English, as determined by initial interactions with our Admissions team
  • be eligible to legally work in the United States, or in Canada if applying for positions in Toronto, for at least 2 years following graduation from the Career Track. See the detailed policy for further requirements about specific Visa types
  • be able to pass any background checks associated with jobs that you apply for
  • apply to positions, dedicate sufficient time and effort, and follow the job search process recommended to you by our career coaches

Note that while our different specialization tracks prepare you for a career in a specialized field, we cannot guarantee that your first data science position will be in that field.

Read the full eligibility criteria and terms here.

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.

How do the tuition payments work?

There are 4 payment options (all of which come with our job guarantee as long as you meet eligibility requirements). Our two standard payment plans are:

  • Monthly Plan: You pay $1,490 per month while you are enrolled in the program. If you take 6 months to graduate, your total payment is $8,940. If you graduate sooner, you pay less!
  • Upfront payment: You pay $7,500 upfront for 6 months. This is a 16% discount on the monthly plan.

In addition, we have 2 other payment options. These are available by application to qualifying US citizens and permanent residents. If you are not a US citizen or permanent resident, you can still apply for financing with a fully qualifying co-borrower who is a citizen or permanent resident - as long as you both have a US address.

  • Deferred Tuition: You pay a $700 deposit upon enrollment to confirm your seat (that's a discount on the normal $1,490/mo plan). Then, you’ll pay the remaining tuition ($11, 800) only when you land a job using your newly learned skills. You can pay that final balance in 18 monthly installments of $655.55. The remaining tuition will be waived if you don’t get a job, and maintain eligibility, within six months of graduating!
  • Climb Credit loan: Available by application to qualifying US citizens and permanent residents. If you are not a US citizen or permanent resident, you can still apply for financing with a fully qualifying co-borrower who is a citizen or permanent resident - as long as you both have a US address.
    • If approved, you pay $500 deposit to confirm your seat. You can finance the remaining $8,440 through a loan. You’ll make small interest-only payments for the first 6 months. After that, you will pay 36 monthly payments of $274-303 each. Learn more here
    • Please note: lending might not be available in all 50 states - click here for the current full lending list.

All charges will be in USD (based on the above prices).If you reside outside the U.S., this might carry an additional transaction fee, depending on the bank you use. We display prices in your local currency to give you an estimate of how much you will pay based on prevailing exchange rates, excluding transaction fees.

I need help with payments. Do you offer financing?

Yes, we have a financing option available! Students can apply for a loan with our partner Climb Credit, and if approved, use it to pay for tuition. Learn about the application process on Climb Credit’s website here.

We do also have a Deferred Tuition payment plan. With this payment plan, you can pay an initial upfront deposit ($700) and then not pay anything else until you graduate. This option is not subject to interest on payment––you will owe a flat fee of $11,800 once you get a job. This fee will also be broken up into monthly payment of $655.55/month over 18 months.

Please note: lending might not be available in all 50 states - click here for the current full lending list.