The Python Data Science Stack

Learn to program in Python (lingua franca of data science), how to follow best coding practices, and start using an ecosystem of useful and powerful Python-based tools

Topics covered: 

  1. Python data science stack
  2. Writing clear, elegant code


16+ hours
The curriculum is split into 9 units, followed by your capstone project and career advice.

Curriculum - what you'll learn

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Learn the most common tools and workflows in Python that make tasks such as acquiring raw data, cleaning it, and getting it into a format amenable for analysis much easier.

Topics covered: 

  1. Pandas for data wrangling 
  2. Data in files and databases 
  3. APIs: Collect data from the internet
Data Wrangling


44+ hours

Data science is also about telling a good story. 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

Data Story
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, it also paves the way for deeper analysis and actual predictive modeling. 

Statistical Inference
16+ hours

Topics covered: 

  1. Theory of inferential statistics 
  2. Parameter estimation 
  3. Hypothesis testing 
  4. Exploratory data analysis


Machine learning combines aspects of computer science and statistics to make useful predictions and recommendations, or automatically find groups and categories in complex data sets. In this module, we'll cover the major machine learning techniques. 

Topics covered: 

  1. Scikit-learn 
  2. Supervised and unsupervised learning 
  3. Top machine learning techniques  best practices
  4. Evaluating and tuning machine learning systems
Machine Learning
60+ hours


In this unit, you’ll take all the Data Science and Machine Learning techniques you’ve learned, and apply them to large-scale data sets, using state-of-the art tools and libraries. You’ll also learn about best practices in taking a Machine Learning prototype to production.

Topics covered:

  1. Work with MapReduce, one of the most popular algorithms for large-scale data manipulation
  2. Understand NoSQL databases and how they differ from SQL
  3. Learn Spark, the state-of the-art in distributed computing frameworks
  4. Learn SparkML and MLlib to implement Machine Learning at scale on Spark
Data Science at Scale
10+ hours


Get the perfect job with unlimited 1:1 career coaching

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

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 the program.

Women held only 26% of data jobs in the U.S.

Women continue to be underrepresented in the tech sector at all levels, despite pledges from the industry’s biggest companies to increase workforce diversity. Pay disparity persists both at startups and larger corporations, leading to a turnover rate that’s twice as high for women as for men. And there’s still a shortage of women studying STEM subjects.

To help make gender parity in tech a reality, we’re providing $750 scholarships for women who enroll in our Data Science Career Track. At Springboard, we believe that everyone should be able to access high-quality, affordable education that they can translate into fulfilling careers. Because a more diverse workforce is a more successful workforce.

Student outcomes


Total students

who have enrolled in the Data Science Career Track since its launch in 2016


Average salary increase

as reported by students who provided pre- and post-course salaries



requested by job guarantee eligible students through November 15, 2018

Develop a portfolio-worthy capstone project

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.

You will work on two capstone projects that involve the following: 

  1. Formulating a problem based on exploratory data analysis; 
  2. Building a model and transforming data so that it can be input to an algorithm; 
  3. Iteratively evaluating performance, and adapting model/data input to figure out if more data or a different algorithm is needed to best solve the problem.

Analysis of response time to pothole repair requests in Chicago

Melanie Hannah

Graduated Jun 2017

See project

A study on animal shelter and outcomes for animals

Irene Yao

Graduated May 2018

See project

More women are breaking into data science. You can too.

Apply to the Data Science Career Track and get $750 as a Women in Tech scholarship

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Student rating on SwitchUp

Work one-on-one with your mentor

Mentor-guided learning not only helps you build skills faster, but also enables career growth.
Have weekly guided calls with your personal mentor, an industry expert.
1:1 Mentorship
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.

Your career coaching calls will help you:

Our graduates were hired by..

Meet a few of our alumni

Karen Masterson

Education: Ph.D. in Linguistics

Previous job: Language IT Specialist

Current job: Data Analyst at

Read her story

Melanie Hanna

Education: BSc. in Chemical engineering

Previous job: Process Engineer

Current job: Jr. Data Scientist at 

Read her story

Structured to fit into your life, guaranteed to get you a job

What you'll learn

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.

Job guarantee

Get a data science job within 6 months of graduating or your money back.

Learn at your own pace with 1-on-1 mentorship from industry experts and support from student advisors and career coaches.


The scholarship of $750 is applicable for Upfront and Month to month payment options.



Pay upfront and save 16% on tuition


Month to month

Pay as you go, only for the months you need


Deferred tuition plan

Pay monthly only after you start a data science job


Climb Credit loan

Finance your education with low monthly payments

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.

Cohorts start the first week of each month

Cohorts start the first week of each month