Our online courses teach a tried-and-true data science curriculum tailored to assure students graduate as well-rounded data scientists. Using real-world tools, students learn from some of the country’s top instructors on Flatiron’s proprietary platform, Learn.co.
From the basics of Python to the complexities of machine learning, our 15-week data science program provides the breadth and depth needed to become a skilled and versatile data scientist. But we don’t stop there: you’ll leave the program with an understanding of the future of data science so you can embark on a fulfilling, lifelong career.
Using your included one-year WeWork hot desk membership — valued at over $2,500 annually — you can connect locally and in person with other students to study in an energizing, beautiful workspace. Enjoy WeWork’s complimentary amenities: high-speed WiFi, 24/7 building access, craft beer on draft, conference rooms, phone booths… plus that fancy fruit water and micro-brewed coffee to help you focus.
Graduate with a new job you love. Our proven job-search framework features 1:1 sessions with a dedicated Ccareer Ccoach, a robust employer pipeline, résumé review, interview prep, and more. All of that is backed with our Tuition-back Guarantee — get a job in six months or your money back (see details).
Each course teaches a proven, living data curriculum that sets you up to be an adaptable and valuable data scientist when you graduate. Though each pace differs in time and structure, you’ll learn the same tried-and-true curriculum no matter which pace you enroll in.
Pick Your Pace
Graduate and become a data scientist in 5 months with our fastest program pace: full-time. Students will work through the 45-50 hours per week of coursework and benefit from dedicated, full-time learning.
Students benefit from learning with a small, cohort and a dedicated Cohort Lead who teaches and mentors throughout the entire course schedule, at a 20:1 student:teacher ratio. Attend live study groups each week with your cohort lead.
Meet 1:1 for a full hour with your Cohort Lead weekly to get help breaking through tough technical concepts. Additionally, connect over 1:1 sessions with a dedicated Educational Coach every 2 weeks to review overall progress stay accountable for your progress. These sessions are in addition to real-time support from our Technical Coaches via our Ask A Question feature in Learn.co.
Graduate and become a data scientist in 5 months with our fastest program pace: full-time. Students will work through the 45-50 hours per week of coursework and benefit from dedicated, full-time learning.
Students benefit from learning with a small, cohort and a dedicated Cohort Lead who teaches and mentors throughout the entire course schedule, at a 20:1 student:teacher ratio. Attend live study groups each week with your cohort lead.
Meet 1:1 for a full hour with your Cohort Lead weekly to get help breaking through tough technical concepts. Additionally, connect over 1:1 sessions with a dedicated Educational Coach every 2 weeks to review overall progress stay accountable for your progress. These sessions are in addition to real-time support from our Technical Coaches via our Ask A Question feature in Learn.co.
Graduate in 10 months at a pace that offers the same structure and rigor as our full-time option, but on a part-time schedule. Students work through a minimum of 25 hours per week of coursework and benefit from a structured schedule designed to keep them on track towards a career in code. While completing the program, students need to dedicate a part of their day-to-day in order to move through the coursework on schedule.
Students benefit from learning with a cohort of up to 40 peers, and a dedicated Cohort Lead who teaches and mentors throughout the entire program schedule. Students dedicate time to a live study groups with their cohort lead every day, with options to fit their schedule.
Meet 1:1 once a month with an Educational Coach to help you stay accountable to your goals, anchor to your motivation, and review your overall progress. Partner with your Coach on addressing challenges, and striking the right balance between your coursework and the rest of your life. These sessions are in addition to to real-time support from our Technical Coaches via our Ask A Question feature.
Graduate in 10 months at a pace that offers the same structure and rigor as our full-time option, but on a part-time schedule. Students work through a minimum of 25 hours per week of coursework and benefit from a structured schedule designed to keep them on track towards a career in code. While completing the program, students need to dedicate a part of their day-to-day in order to move through the coursework on schedule.
Students benefit from learning with a cohort of up to 40 peers, and a dedicated Cohort Lead who teaches and mentors throughout the entire program schedule. Students dedicate time to a live study groups with their cohort lead every day, with options to fit their schedule.
Meet 1:1 once a month with an Educational Coach to help you stay accountable to your goals, anchor to your motivation, and review your overall progress. Partner with your Coach on addressing challenges, and striking the right balance between your coursework and the rest of your life. These sessions are in addition to to real-time support from our Technical Coaches via our Ask A Question feature.
Our self-paced program provides the same rigorous curriculum and mastery standards of our full-time and part-time paces, but at a 100% flexible, self-guided schedule. This program most benefits students who have familiarity with data science and unpredictable schedules by providing access for up to 15 months as they guide themselves through the coursework.
Includes five sessions with an Educational Coach to help you set and stay accountable to your goals, and make steady progress at a pace that is right for you. Students also get on-demand access to Technical Coaches through the Ask A Question feature in Learn.
Collaborate with fellow students and teachers, join live study groups, pair and chat with your peers, and access a living course that features thousands of updates a year to reflect current industry trends.
Our self-paced program provides the same rigorous curriculum and mastery standards of our full-time and part-time paces, but at a 100% flexible, self-guided schedule. This program most benefits students who have familiarity with data science and unpredictable schedules by providing access for up to 15 months as they guide themselves through the coursework.
Includes five sessions with an Educational Coach to help you set and stay accountable to your goals, and make steady progress at a pace that is right for you. Students also get on-demand access to Technical Coaches through the Ask A Question feature in Learn.
Collaborate with fellow students and teachers, join live study groups, pair and chat with your peers, and access a living course that features thousands of updates a year to reflect current industry trends.
Not sure which pace is right for you? Schedule a 10-minute consultation with our Admissions team to determine which learning options fits you best.
Job-seeking Online Web Developer Program (now called the Online Software Engineering Bootcamp) students in the most recent Online Outcomes Report who took full-time salaried roles, paid apprenticeships, and part-time roles during reporting period
Job-seeking Online Web Developer Program (now called the Online Software Engineering Bootcamp) students in the most recent Online Outcomes Report who took technical roles
More than ever before, industries are capturing data on a variety of topics, behaviors, and trends. There are stories to tell or insights to share in that data. Without data science, this information stays stuck. To innovate and set business goals, more and more companies are looking to data scientists to fill in the gaps and find opportunities never before considered or understood.
In fact, data scientist and machine learning engineer jobs are the two fastest-growing careers in all of technology.
As this area of expertise has grown, the positions within the field become more nuanced. After completing our Flatiron School’s Online Data Science Bootcamp — at any pace — students will be qualified to secure a job as a data scientist, but can also consider pursuing any of the following related positions:
Our career-ready Data Science curriculum provides the technical skills, expertise, and tools necessary to think and work as a data scientist. Working in our WeWork classroom with our seasoned instructors, you’ll master a mix of software engineering and statistical understanding, then apply both skills in new and challenging domains.
Our robust Data Science program ensures not only job readiness for today’s growing job market, but the aptitude to continue learning and stay relevant in your career for years to come.
Our Data Science program moves quickly and our passionate students embrace that challenge. While no experience is necessary to apply, we require you to demonstrate some data science knowledge prior to getting admitted, then complete a prework course before Day 1. To help you prepare for our bootcamp, we provide a free introductory course. This prework ensures that you come in prepared and able to keep pace with the class.
Our first module introduces the fundamentals of Python for data science. You’ll learn basic Python programming, how to use Jupyter Notebooks, and will be familiarized with popular Python libraries that are used in data science, such as Pandas and NumPy. Additionally, you’ll learn how to use Git and Github as a collaborative version control tool. At the end of this module, you’ll be able to build a basic linear regression model and evaluate the results. Finally, we’ll conclude with a heavy focus on visualizations as a way to convert data to actionable insights.
Variables, Booleans and Conditionals, Lists, Dictionaries, Looping, Functions, Data Cleaning, Pandas, NumPy, Matlotlib/Seaborn for Data Visualization, Git/Github
In this module, you’ll learn about data structures, relational databases, ways to retrieve data, and the fundamentals of SQL for data querying for structured databases, as well as NoSQL (and MongoDB) for non-relational databases. Furthermore, we’ll cover the basics of HTML, XML, and JSON in order to access data from various sources using APls, as well as Web Scraping.
Data structures, Relational Databases, SQL, Object-Oriented Programming, NoSQL databases, MongoDB, JSON, HTML/XML, Accessing Data Through APIs, CSS Web Scraping
This is a basic module that introduces the fundamentals of probability theory, where you’ll learn about principles like combinations and permutations. You’ll continue with statistical distributions and learn how to create samples with known distributions. By the end of this course, you’ll apply your knowledge by running Monte Carlo simulations and AB tests.
Combinatorics, Probability Theory, Statistical Distributions, Bayes Theorem, Naive Bayes Classifier, Sampling Methods, Monte Carlo Simulation, Hypothesis Testing, AB Testing
We’ll cover how and when regression models can be used to transform data into insights. You’ll learn about both linear and logistic regression and the algorithm behind regression models. By the end of this module, you’ll be able to evaluate the results of regression models and extend them to interaction effects and polynomial features. To compare the performance of models built, you’ll dive deeper into model evaluation and the bias-variance trade-off.
Linear Algebra, Linear Regression and extensions, Polynomials, Interaction effects, Logistic regression, Optimization Cost Function, Gradient Descent, Maximum Likelihood Estimation, Time Series Modeling, Regularization and Model Validation
In Module 5 you’ll learn how to build and implement machine learning’s most important techniques and will take your first steps into classification algorithms through supervised learning techniques such as Support Vector Machines and Decision Trees. Additionally, you’ll learn how to build even more robust classifiers using ensemble methods like Bagged and Boosted Trees, as well asRandom Forests. Next, you’ll move onto unsupervised learning techniques such as Clustering, and dimensionality reduction techniques like Principal Component Analysis.
Distance Metrics, K Nearest Neighbors, Clustering, Decision Trees, Ensemble Methods, Dimensionality Reduction, Pipeline Building, Hyperparameter Tuning, Grid Search, Scikit-Learn
In the final module, you’ll learn how to use regular expressions in Python and how to manage string values, analyze text, and perform sentiment analysis. Additionally, you’ll get an in-depth overview of deep learning techniques, densely connected neural networks for high-performing classification performance, convolutional neural networks for image recognition, and recurrent neural networks for sequence modeling. You’ll also learn about techniques to evaluate performance and to optimize and regularize model performance.
Neural Networks, Convolutional Neural Networks, Ngrams, POS Tagging, Text Vectorization, Context-Free Grammars, Neural Language Toolkit, Regular Expressions, Word2Vec, Text Classification
In our final project, you’ll work individually to create a large-scale data science and machine learning project. This final project provides an in-depth opportunity for you to demonstrate your learning accomplishments and get a feel for what working on a large-scale data science project is really like. You and your fellow students will each pitch three different ideas and then decide on your final project with your instructors. Instructors advise on projects based on difficulty and feasibility given the time constraints of the course. At the end of the course, you’ll receive a grade based on various factors. Upon project completion, you’ll understand how to construct a project that gathers and builds statistical or machine learning models to deliver insights and communicate findings through data visualisation and storytelling techniques.
“Data Science is leading the way in changing how people and businesses make decisions. With that in mind, we’ve developed a curriculum that teaches the skills necessary for the field, but also creates an environment that cultivates the curiosity all great data storytellers share.”
At Flatiron School, students learn by building. Students will come away with an advanced Portfolio Project to demonstrate their technical proficiency and creativity to current or future job managers and hiring leads.
Our course dedicates significant time towards completion of a large-scale data science and machine learning project where students work on a solo project in a domain of their choice. The project provides an in-depth opportunity for students to demonstrate their mastery of material, review course subjects, and work on an end-to-end data science project.
GitHub is the modern source of technical resumes. Students push every line of code they write at Flatiron School to GitHub through our proprietary platform, Learn.co, giving them an extensive profile to show employers and fellow data scientists.
Students build their credibility as data scientists and immerse themselves by attending — and challenging themselves to present — at Flatiron School events.
GitHub is the modern source of technical resumes. Students push every line of code they write at Flatiron School to GitHub through our proprietary platform, Learn.co, giving them an extensive profile to show employers and fellow data scientists.
Students build their credibility as data scientists and immerse themselves by attending — and challenging themselves to present — at Flatiron School events.
Final projects will be unique for each student and determined in partnership with the student’s instructor. Specifically, projects are required to have the following items to meet the minimum bar of difficulty:
Examples of final projects could be building a better search engine for a travel site (such as Airbnb or Kayak) or an examination of a global interest utilizing data visualization and topic modeling.
At Flatiron School, we take teaching seriously and know that great teachers inspire us to understand topics on a profound level. With experience both in the field and in the classroom, our data science instructors are dedicated and thorough. Simply put: you’ll learn from the best.
At Flatiron School, you won’t just learn data science. You’ll also learn how to be an effective job seeker and no-brainer tech hire. With 1:1 career coaching, a robust employer network, and a proven job search framework, our Career Services team is committed to helping you land the job you want.
Every student is paired with a dedicated career coach, who coaches students through an effective job search via resume review, mock interviews, and partnering with students on creating and executing strategies for building a job opportunity pipeline and getting a foot in the door at top-choice companies.
Flatiron students change careers with confidence thanks to our money-back guarantee: you’ll receive a job offer within six months, or we’ll refund your full tuition. (See eligibility terms.)
Our team of Employer Partnerships Associates does nothing but evangelize for you. We’re constantly in touch with companies on your behalf, helping them understand the value of hiring a Flatiron School grad, and connect with graduates of the school.
After years of helping students get hired, we’ve developed a proven framework for leading a successful job search. Nearly every single student who has followed these guidelines has been hired.
| Time Until Career-Ready | |||
| Time commitment | |||
| Career Services Support |  | | |
| 1,000+ Curriculum Hours | | | |
| Educational Coaching | | | |
| Live Lectures | | | |
| Assigned Cohort Lead | | | |
| Assigned Peer Group | Average of 20 students | Average of 40 students | |
| Technical Mentorship | One hour weekly | Half-hour weekly | |
| WeWork Hotdesk Membership | | | |
| Tuition | |||
| Money-Back Guarantee | | | |
Dedicated to making our programs more accessible, we offer competitive financing options through Skills Fund and Climb, two industry-leading accelerated learning financing companies.
You can now defer your online tuition with the Flatiron School Income Share Agreement, available in select states. There is no deposit required when you enroll, and the reminder of you tuition is paid once you’ve left the program and are earning a minimum income of $3,333.33 per month, annualized to $40,000 per year.
As a part of our ongoing effort to support diversity in tech, Flatiron is pleased to offer various scholarships to qualified women, minorities, and veterans, as well as merit-based scholarships. Schedule a Q&A with our Admissions team to hear more about our open scholarships.
With a Deferred Payment Plan (DPP), you pay nothing to your tuition until after you’ve left Flatiron School and meet the minimum income threshold. Your tuition payments only begin once you’ve left the program and are earning at least a minimum monthly income.
As a part of our ongoing effort to support diversity in tech, Flatiron is pleased to offer various scholarships to qualified women, minorities, and veterans, as well as merit-based scholarships. Schedule a Q&A with our Admissions team to hear more about our open scholarships.
Start your journey to a career as a data scientist by joining our inclusive, dynamic student community. At Flatiron School, we admit students who bring creativity, ingenuity, and curiosity to the classroom — all you need is passion and an open mind.
Application steps
What we look for
Submit a written application to our Admissions team. Tell us about yourself and why you want to learn to become a data scientist.
We love data science, and bring together people who see it as a craft and want to be great at it — not just for their careers or as a means to an end, but as an end in and of itself.
Chat with an Admissions Advisor in a non-technical interview. This is an opportunity for us to get to know each other a little better. Nothing technical — just a friendly conversation.
Flatiron School students are driven. While we look for students with an ability to transfer between different skill sets easily, aptitude for data science is built around an innate curiosity for the world and how people live in it.
After writing and submitting some code on Learn.co, you’ll attend a live coding session with an instructor to assess your understanding of the material covered in the pre-work. You’ll then be notified of your status within 4 business days.
We don’t admit students. We craft a class. A lawyer, journalist, and pro athlete will do more interesting things together than three of any one background.
Submit a written application to our Admissions team. Tell us about yourself and why you want to learn to become a data scientist.
Chat with an Admissions Advisor in a non-technical interview. This is an opportunity for us to get to know each other a little better. Nothing technical — just a friendly conversation.
After writing and submitting some code on Learn.co, you’ll attend a live coding session with an instructor to assess your understanding of the material covered in the pre-work. You’ll then be notified of your status within 4 business days.
We love data science, and bring together people who see it as a craft and want to be great at it — not just for their careers or as a means to an end, but as an end in and of itself.
Flatiron School students are driven. While we look for students with an ability to transfer between different skill sets easily, aptitude for data science is built around an innate curiosity for the world and how people live in it.
We don’t admit students. We craft a class. A lawyer, journalist, and pro athlete will do more interesting things together than three of any one background.
Talk with our admissions team — they’re here to help.
Full-time and part-time courses have specific starting dates, while self-paced students can start at any time.
While there are no prerequisites to our online data science course and we welcome beginners, we do recommend exploring our free Data Science Bootcamp Prep course before applying. It’s important for two key reasons:
That depends on a few important factors. What’s your learning style? Where are you in life right now? What kind of experience are you looking for?
We recommend thinking of it like exercise. Some people just need a pair of sneakers and can run outside. Some people want access to the best equipment so they join a gym, or to be part of a community and they do Crossfit. Some people want to take organized classes, and some need to go away for yoga retreats and focus on nothing but that. Ultimately, there’s no right or wrong way to get fit. It’s about knowing your goals and knowing what brings the best out of you.
The same is true with learning. Do you want a rigid schedule or to learn at your own pace? Do you do better in a quiet environment or surrounded by people? Do you want to focus on this full time or not?
Here are a few other things that may help:
End Goal: All programs are focused on getting you a job as a data scientist after graduation. Although the in-person immersive is based in New York City, each program offers placements all over the United States.
The first step is to fill out a written application. Once submitted, you should hear back from our admissions team on the next step within 2 business days. If your application is chosen to move forward, you will be invited to schedule a video call with a member of the admissions team to get to know you better. After this point, students receive an admissions decision within a few business days. Students must complete a technical interview when applying to the full-time or part-time course pacing options.
Our modular structure means you’ll always know that you’re gaining the competencies to become a data scientist— and it gives us the opportunity to see who might need more mentorship to get there. Because our curriculum builds cumulatively, each module concludes with a 1:1 instructor review to check in on your progress and make sure you’ve gained a strong understanding before we add more concepts on top of it in the next module. If you don’t pass the review, you’ll receive additional direct mentorship to solidify your understanding and take it again. If you don’t pass this time, you’ll have the opportunity to repeat the full module. You will have a limited number of repeats available for your chosen program, after which you will be asked to leave the program for a partial refund. Partial refunds are determined based on the number of weeks in the program. For more information contact admissions@flatironschool.com.
Once you have been accepted into the program, you may apply for financing through one of our lending partners. We work with Skills Fund and Climb, who have helped many Flatiron students secure loans. We recommend waiting until after you have been accepted into the program before applying for a loan.