No prerequisites • Remote • Flexible schedule • Job guarantee

Data Science Course: Foundations to Core. Go from Beginner to Data Scientist. Job Guaranteed.

Learn data science, Python and machine learning on your schedule. In under 8 months our flexible, remote program will help you land your dream job with 1-on-1 support at every step. If you don't land a job in 6 months after graduating, you'll get a full refund.

Our graduates have been hired by top tech companies

From apprentice to expert, transform your career from scratch

Whether you’re new to data or a working analyst, launch your data science career in just 8 months part-time. Our flexible, human-guided curriculum featuring advanced specialization, means you can learn when you want, with support as you need it.

Learning that fits your schedule

With our remote, project-based curriculum, learn to code when it suits you, so you don’t have to put your life on hold.

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.

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.

Our Foundations to Core curriculum was built for beginners

There are no prerequisites to start Foundations to Core. You’ll learn key concepts, master Python programming and pass the skills survey, which you can take at any time, before starting the core curriculum. If you're already comfortable with Python, you'll start the core curriculum immediately.

Data Science Foundations to Core
Data Science Career Track
Prior Python experience required
Data Science Foundations to CoreNo
Data Science Career TrackYes
Course length (part-time)
Data Science Foundations to Core8 months
Data Science Career Track6 months
Foundations curriculum
Data Science Foundations to CoreKey concepts, Python intro - advanced
Data Science Career TrackN/A
Career track curriculum
Data Science Foundations to CoreData science and machine learning
Data Science Career TrackData science and machine learning
Job guarantee eligible
Data Science Foundations to CoreYes
Data Science Career TrackYes
Data Science Foundations to CoreYes
Data Science Career TrackYes
Career coaching
Data Science Foundations to CoreYes
Data Science Career TrackYes
Upfront tuition
Data Science Foundations to Core$9,900
Data Science Career Track$9,900

Our award winning programs land students jobs

92.5% of our data science graduates receive a job offer within 12 months of graduation.
Data Science
Data Science
All categories

What you will learn in this data science course

The 500+ hour curriculum includes articles, videos, practice exercises, career-related coursework and 3 capstone projects. The final capstone provides you the option to specialize as a generalist, business insider or continue advancing in machine learning. Studying 20-25 hours per week, you should complete it in 8 months or less.

Foundations: Beginner to advanced Python
Data Wrangling
The Data Story
Statistical Inference
Machine Learning
Software Engineering for Data Science
Data Science at Scale
Advanced Machine Learning

Learn the fundamental data science and probability concepts before getting hands-on with introductory to advanced Python programming units. Students typically finish in 6-8 weeks part-time, however you can choose to complete them faster. Progress to the core curriculum by passing the technical skills survey, which can be taken at any time.

  • Introduction to data science
  • Foundations of probability
  • Introduction, intermediate, advanced Python
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

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

Data science bootcamp start dates

Data Science Foundations to Core is a 6-8 month program. Most students devote 15-20 hours a week to complete the course.


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

Scholarship eligibility: Are you a woman or a veteran?
Upfront discount
Pay upfront and save 13% on tuition
Paid at the time of enrollment
Total cost
Month to month
Pay only for the months you need, up to 6 months
$1,890 /mo
Total: Up to $11,340
Paid at the time of enrollment
Monthly payments during course
Total cost
Variable (up to $11,340)
Deferred tuition plan
Pay monthly only after you start a data science job
$450 /mo
Total: $16,900
Paid at the time of enrollment
$700 refundable deposit
Monthly payments during course
Monthly payments after course
$450 for 36 months after starting new job
Total cost
* only available for U.S. citizens/permanent residents
Climb Credit loan
Finance your education with low monthly payments
$57 - $152*/mo
Total: $12,804 - $15,314*
Paid at the time of enrollment
Monthly payments during course
$57 - $152* (interest payments only)
Monthly payments after course
$346 - $400* for 36 months
Total cost
$12,804 - $15,314* (Loan amount of $10,840)
* 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 Foundations to Core Data Science Bootcamp

Secure your spot now. Spots are limited, and we accept 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

What are the prerequisites for admission?

The Data Science Foundations to Core course has no prerequisites. It includes foundational units helping you learn key concepts and master Python before progressing to the core Data Science Career Track curriculum.

If you’re already familiar with Python, you won’t be required to complete these units and will start in the core Data Science Career Track. During the enrollment process you’ll complete a technical skills survey which will help us gauge your ideal starting point.

How does the admissions 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 5 minute questionnaire to learn about your prior educational and work experience. You’ll then have a brief phone call with one of our Admissions Directors to discuss your experience before taking a technical skills survey to determine your best starting point. You may begin in the foundations curriculum or skip straight to the core course depending on the results.

How long does this course take?

The course includes a 500 hour core career track curriculum plus 40 hours of foundational units. Students are expected to graduate in 8 months working 15-20 hours per week, however you may choose to dedicate more time and complete sooner.

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.