Become a Data Scientist

Get a job, or your money back.

Introducing Career Track:
online, mentor-guided bootcamp, designed to get you hired.

Request a syllabus
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Your Springboard To A Data Science Career

Enroll in Data Science Career Track, and you’ll get hired within 6 months of graduating, or we’ll refund 100% of your tuition.

In this online bootcamp, you will master the data science process, from statistics and data wrangling, to advanced topics like machine learning and data storytelling, by working on real projects. With the guidance of your personal mentor and career coaches, you will graduate with an interview-ready portfolio and a network of data scientists.

We won’t stop there. We know that career transitions are hard, and we’ll support you every step of the way — until you get hired.

Build Data Science Career Skills

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Master data science topics

Learn machine learning, inferential statistics, and data storytelling by working on lifelike projects, designed by industry experts

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Learn with a community

Weekly calls with your own data science mentor. Stay accountable, and get the feedback you need

Prepare for career transition

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Personalized career guidance

1-on-1 sessions with a data science career coach. Build your list of target companies, and perfect your pitch

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Ready for interviews

Mock interviews with data scientists. Expert reviews of your resume, portfolio and LinkedIn/Github profiles

Land your dream job

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Access to our network

Exclusive access to a network of hiring companies who can get your data science career started.

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Get a job, guaranteed.

We’ll work overtime to help you get a job within 6 months of graduation, or your money back!

Our students are working at

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Meet a few of our alums

More success stories

Your own mentor.

With your weekly mentor call, you’ll get to
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Learn from the best
Set your own agenda
Get inspired

Your mentor is already working in the industry and will give you valuable insights.

Discuss deliverables, topics you are interested in, or career steps.

Our students love being inspired and motivated by their mentors.

Meet our mentors

Our world-class mentors are hand-picked, for their experience and love of teaching.

Learn online with the best curriculum on the web

How Springboard will prepare you for a career in Data Science (1m51s)

Raj Bandyopadhyay, Director of Data Science at Springboard

Curriculum built by industry

Built by experts from IBM, Cisco and Pindrop Security, our curriculum combines the best data science learning resources. We update it regularly, so you're up to speed with the latest from the industry.

Real projects

We believe you learn best by doing. Our ~200 hour curriculum is designed around 18 real-life projects. Graduate with a portfolio that you can show to employers. Earn a certificate of completion, signed by your mentor.

Career prep and resources

From charting your job search strategy to technical interview prep, our data science career resources will give you the skills and confidence to ace those interviews and land your dream job.

Curriculum - what you’ll learn

The curriculum is split into 7 units, followed by your capstone project and career advice.

Python is one of the languages that has become the lingua franca of data science (the other being R). In this module, you'll learn to program in Python and start using an ecosystem of useful and powerful Python-based tools for doing data science and building an online portfolio.

Topics Covered

  • Python
  • iPython Notebook
  • Matplotlib
  • Pandas
  • Git and Github

Estimated Time: 10+ Hours

It is estimated that data scientists in industry spend the most time on data wrangling i.e. cleaning the raw data and getting it into a format amenable for analysis, usually with the help of semi-automated tools. In this module, you'll learn the most common tools and workflows in Python that make this normally onerous task a snap.

Topics Covered

  • Deep Dive into Pandas for Data Wrangling
  • Data in files: Work with a variety of sources from unstructured/semi-structured text files (.txt) to delimited/structured/nested format files like excel, csv, json, xml etc.
  • Data in Databases: Get an overview of relational and NoSQL databases and practice data manipulation with SQL.

Estimated Time: 17+ Hours

If there's one thing that most data scientists would have loved to know before they entered the field, it's that 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 on the results of their work. A data story is a powerful way to present insights to your clients, combining visualizations and text into a narrative. But storytelling is an art, and needs creativity. This section will try to get your creative juices flowing by suggesting some interesting questions you can ask of your dataset, and a few plotting techniques you can use to reveal insights.


You’ll practice the concepts learned by creating a data story.

Estimated Time: 10+ Hours

Statistics is the mathematical foundation of data science. Within statistics, inferential statistics is a set of techniques that helps us identify significant trends and characteristics of a data set. Not only is it useful to explore the data and tell a good story, but also opens the way for deeper analysis and actual predictive modeling. In this module, we cover several important inferential statistics techniques in detail.

Topics Covered

  • Theory and application of inferential statistics
  • Parameter estimation
  • Hypothesis testing
  • Statistical significance
  • Correlation and regression
  • A/B Testing

Estimated Time: 13+ Hours

Machine Learning combines aspects of computer science and statistics to extract useful insights and predictions from data. Machine Learning is what lets us make useful predictions and recommendations, or automatically find groups and categories in complex data sets. In this module, we'll cover the major kinds of machine learning algorithms (supervised and unsupervised), with several techniques within each of them. You'll learn when these algorithms are useful, the assumptions they incorporate, the tradeoffs they involve and the various metrics you can use to evaluate how well your algorithm performs. 

Topics Covered

  • Scikit-learn
  • Supervised and unsupervised learning
  • Fundamentals: Regression, Naive Bayes, SVM, Decision trees, Clustering
  • Advanced: Recommender systems, Anomaly detection, Time series analysis
  • Validation and evaluation of machine learning
  • Feature engineering
  • Best practices for applying machine learning

Estimated Time: 53+ Hours

Have you seen the stunning interactive visualizations on news websites such as New York Times or FiveThirtyEight? Have you wondered how those are created? These advanced interactive visualizations not only look great and show your skills, but are also excellent tools for exploring complex, high-dimensional data sets.

Topics Covered

  • D3.js
  • Seaborn
  • Bokeh
  • Plotly

Estimated Time: 5 Hours

You now know how to work with data sets that easily fit in the memory of your laptop. But what happens when that's not the case? A data scientist often has to know how to scale these analyses and algorithms to really huge data sets. This is where "Big Data" technologies like Hadoop and Spark come in. Hadoop is an open-source implementation of map-reduce, one of the first major algorithmic innovations in big data, and arguably the algorithm that allowed Google to become the behemoth it is today. Spark is Hadoop's newer, younger cousin -- a technology that addresses some glaring flaws and inefficiencies in Hadoop, and allows many complex machine learning and other analytical techniques to be implemented at scale in highly efficient ways.

Topics Covered

  • Intro to Big Data
  • MapReduce
  • Spark
  • MLib
  • NoSQL

Estimated Time: 10 Hours

In this program, you'll complete two Capstone Projects for your portfolio. You'll work on the first project as you go through the main part of the curriculum, and on the second project as you're focused on your job search. 

The Capstone Project is a key part of our curriculum that every student must complete. The project is designed to provide you with the experience of working in a realistic data science scenario. Working with your mentor, you'll pick a data set and a problem of interest. From the start to the finish, your project will be targeted to a specific client (real or imaginary). Using the data science techniques you've learned, you'll not only come up with a reasonable solution to the problem, but learn to present it to them as a compelling story. 

Estimated Time: 50 Hours

We provide career material at strategic points both in the curriculum as well as via calls with our expert career support coach. We'll help you create a tailored job search strategy based on your background and goals, teach you how to evaluate companies and roles, show you how to effectively get and ace interviews, and negotiate on salary. 

Topics Covered

  • Anatomy of a tech company
  • The job search strategies that top candidates use
  • How to build your network and effectively use it to land interviews
  • Create a high-quality resume, LinkedIn profile and cover letter
  • Interview coaching and practice, including mock interviews for both technical and non-technical topics
  • Negotiation success tips

Estimated Time: 35 Hours

Get a detailed course syllabus in e-mail:

Who is this workshop for?

The Data Science Career Track is for

people with a prior background in statistics and programming.

How much prior experience is needed?

Most students in this course will:
(1) have completed a college-level statistics class, or have equivalent knowledge, AND
(2) know programming well enough to be comfortable picking up a new language using resources on the web.
Other than that, all professional and academic backgrounds are welcome. We've taught software developers, grad students, analysts, and BI / finance professionals.

Not sure if your background is a fit?

Write to us at Lina, our Program Advisor will help you think through the decision.

No math/programming background? See Foundations of Data Science

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Kane Li, Student Advisor

We’re with you every step of the way

We’re not going to pretend that this course is easy street. This is a serious commitment, with real rewards.

The good news? We’ve helped thousands of aspiring data scientists like you level up their skills and advance their career.

You commit to put in the hard work and time. We are committed to support you at every step, and help you succeed.

Schedule & Price

The next class starts on:

April 24th 2017

Deadline for applications is April 10th, 2017. That's in:

15 Days 23 Hours

Start My Application

Tuition and payment options

Upfront for 6 months Month to month
Benefit Most affordable, save 20% by paying upfront Pay as you go, only for the months you need
Paid at the time of enrollment $4,800 $1,000
Monthly payments -- $1,000
Total cost $4,800 Variable (capped at $6,000)

We estimate the total effort required at ~200 hours. If you devote 8-10 hours per week, you should expect to complete in 5-6 months.

To read the terms of the job guarantee, head to the FAQ below.

Apply for Data Science Career Track

Ready to take your career to new level? Apply now!

Spots are limited, and we'll accept qualified applicants on a first-come-first-served basis. Apply early to secure your spot.
Start My Application

data science careerThe application will take 5-10 mins

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Full refund within 7 days if you are not happy with the course.

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Full refund if you don’t get a job within 6 months of completion.

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Complete the course at your own pace. You pay for the course month-by-month.

Frequently Asked Questions

  • You must be 21 years or older.
  • You must be proficient in spoken and written English.
  • You must be eligible to legally work in the United States for at least 1 year following graduation from the program.
  • You must be willing to apply to and accept jobs in one of our 11 supported metropolitan areas in the US.
  • You must satisfactorily complete all requirements for graduation
Read the full eligibility criteria and terms here.
There are two payment options:
  • Monthly Plan: You pay $1,000 per month while you are enrolled in the program, capped at $6,000. After 6 months in the program, we will stop billing you. If you take 6 months to graduate, your total payment is $6,000. If you graduate sooner, you pay less!
  • Upfront payment: You pay $4,800 upfront for 6 months. This is a 20% discount on the monthly plan.
Your tuition includes:
  • 200-hour curriculum of technical and career materials curated by industry experts.
  • Weekly 1-1 video calls with your personally matched mentor.
  • Access to an exclusive community and Office Hours with mentors, career coaches and peers.
  • Dedicated community managers to answer questions and give feedback on projects within a day.
  • Personalized feedback to help you polish your resume, portfolio and social profiles
  • 1-on-1 session with a data science career coach to personalize your pitch and job-search strategy
  • Lots of interview practice via 1-on-1 mock interviews (behavioral and technical)
  • Exclusive access to an employer network
  • 100% money-back guarantee if you can't find a job in 6 months
  • All taxes and fees.
We estimate that on average, students will take about 200 hours. The exact amount of time can vary based on your background, and learning style.
You should expect to spend at least 7-10 hours per week on the course. Depending on your desired pace, we’ll work with you to create a course plan at the beginning of the course.
We work with industry experts to pick determine the most relevant Data Science topics, and find the best resources on each topic (e.g. videos, tutorials, lectures).

Note that many of the videos, etc. in the curriculum are not created in-house by us. Instead, we find and curate the best resources available on the subject. Think of us as a college professor who creates a syllabus by combining the best textbook chapters, articles, papers, and projects (instead of teaching from only her own textbook).

We believe the curated curriculum is our unique strength. By standing on the shoulders of giants, we’re able to update the curriculum frequently, and always teach the latest tools and technologies.
You’ll have support from
  • Your mentor: Data science expert for weekly 1:1 guidance and accountability
  • Community Teaching Assistants: 24x7 help when you’re stuck, and detailed feedback on each project
  • Career coaches: Schedule for resume reviews, mock interviews, etc.
  • Springboard student advisors: Develop lessons plans, or get help with any aspect of the program
And finally, your classmates: Form study groups, or work on projects together!
We will provide certificates of completion to all the participants who complete the workshop and successfully complete all the projects.
The workshop will happen in a completely online, self-paced, mentor-aided format. All you need is an internet connection.
You should have a strong background in Probability & Statistics, and should be very comfortable enough in programming to pick up a new language using resources on the web. If you do not meet these requirements, please check out our Foundations of Data Science workshop instead.
Spots are limited and we will accept most qualified candidates first. The first step involves of a 10-minute questionnaire. 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 Career Track is a good fit for you.
Our partners include consulting, healthcare, education, finance, manufacturing, technology and security companies. We have hiring partners in all metropolitan areas where the job guarantee is offered.