FLEXIBLE SCHEDULE • REMOTE • MENTORSHIP • CAREER COACH• JOB GUARANTEE
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.
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.
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.
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.
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.
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).
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.
Swipe to see more mentors
See more mentors
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.
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.
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
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
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.
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.
Secure your spot now. Spots are limited, and we accept qualified applicants on a first come, first served basis.
All our courses take place entirely online. All you need is an Internet connection.
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.
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.
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.