Data Science

Data Science
in
Houston
NYC Atlanta Chicago Houston Online London Seattle Washington, D.C.

  • 15-Week Career Change Fast-Track
  • Career Services & Money-Back Guarantee (see details)
  • Downtown Houston Campus Location

Data science is one of the fastest-growing job titles in the tech industry, with Python, SQL, and proficiency with machine learning being some of the most sought out skills to help companies grow and make informed decisions. With Flatiron School’s proven, industry-leading data science bootcamp, learn the skills necessary to reinvent yourself as a professional data scientist and change your life.

Location
Houston
NYC Atlanta Chicago Houston Online London Seattle Washington, D.C.
Overview

Establish yourself as a highly skilled, highly employable data scientist

Quality learning comes at the intersection of diligence and curriculum. With that vision in mind, Flatiron School has brought together passionate, experienced instructors and ambitious students to achieve incredible outcomes since 2012. And now we’re bringing that vision to data science with our immersive Data Science program.

Houston’s First On-Campus, Immersive Data Science Course

We’re the first bootcamp in Houston to offer a full-time, on-campus data science course that graduates students in as little as 15 weeks. From Python to Machine Learning, our 15-week program gives students the breadth and depth needed to become well-rounded data scientists.

Money-Back Guarantee

We’re the only bootcamp with a Houston campus that provides a money-back guarantee (see details) if you don’t get a job offer within 6 months of graduating.

Successful Graduates

Flatiron School graduates have not only found jobs, but have also found jobs they love. Read about one of our Houston alumni, Josh.

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Curriculum

What You'll Learn: Data Science & Machine Learning

Over 15 challenging weeks at Flatiron School’s campus, students will learn how to gather data, apply statistical analysis to answer questions with that data, and make their insights and information as actionable as possible. Our course load ensures not only job readiness for today’s market, but also the skills to keep learning and stay relevant.

Week

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Foundations of Data Science Libraries

Students will gain an overview of the skills of understanding data structures, data gathering and data cleaning.

Python & SQL

Students will learn fundamental concepts in programming using Python and SQL to gather and clean data.

Linear Regression Model

Students will learn what statistical distributions are, and how to run a linear regression model.

  • Foundations of Data Science Libraries

    Students will gain an overview of the skills of understanding data structures, data gathering and data cleaning.

  • Python & SQL

    Students will learn fundamental concepts in programming using Python and SQL to gather and clean data.

  • Linear Regression Model

    Students will learn what statistical distributions are, and how to run a linear regression model.

Frequentist & Bayesian Statistics

Students will learn about Bayesian and Frequentist statistics so that they can go deeper into analyzing information with statistics.

Repeated Random Sampling

Students will learn about Monte Carlo simulations and Markov Process. Then students will revisit experimental design techniques and apply their deeper statistical knowledge to A/B testing a website.

Building & Validating Regression Models

Students will learn how the Ordinary Least Squares method and gradient descent in a linear regression work.

  • Frequentist & Bayesian Statistics

    Students will learn about Bayesian and Frequentist statistics so that they can go deeper into analyzing information with statistics.

  • Repeated Random Sampling

    Students will learn about Monte Carlo simulations and Markov Process. Then students will revisit experimental design techniques and apply their deeper statistical knowledge to A/B testing a website.

  • Building & Validating Regression Models

    Students will learn how the Ordinary Least Squares method and gradient descent in a linear regression work.

Supervised Learning: Non-Parametric Algorithms

Students will learn about decision tree learning and about ensemble methods such as bagging, boosting and random forests.

Unsupervised Learning Techniques

Students will learn clustering techniques like k-means and hierarchical clustering, and dimensionality reduction techniques, such as Principal Component Analysis.

Time Series Modeling

Students will learn how to to analyze time series data (such as stock market prices, temperature, sales… over time) using Panda.

  • Supervised Learning: Non-Parametric Algorithms

    Students will learn about decision tree learning and about ensemble methods such as bagging, boosting and random forests.

  • Unsupervised Learning Techniques

    Students will learn clustering techniques like k-means and hierarchical clustering, and dimensionality reduction techniques, such as Principal Component Analysis.

  • Time Series Modeling

    Students will learn how to to analyze time series data (such as stock market prices, temperature, sales… over time) using Panda.

Regular Expressions

Students will learn how to manage string values, analyze text and perform sentiment analysis in Python.

Big Data

Students will learn how to use PySpark, a distributed programming framework which makes working with huge datasets feasible.

DS_PDP

Deep Learning Techniques

Students will learn about densely connected neural networks, for highly performant classifiers, convolutional neural networks for image recognition, and recurrent neural networks, for sequence modeling.

  • Regular Expressions

    Students will learn how to manage string values, analyze text and perform sentiment analysis in Python.

  • Big Data

    Students will learn how to use PySpark, a distributed programming framework which makes working with huge datasets feasible.

  • DS_PDP

    Deep Learning Techniques

    Students will learn about densely connected neural networks, for highly performant classifiers, convolutional neural networks for image recognition, and recurrent neural networks, for sequence modeling.

Create a large scale data science and machine learning project

How to construct a project that gathers, explores, builds statistical or machine learning models to deliver insights and communicate findings with data visualization and storytelling techniques.

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A day in the life at Flatiron School Houston
Student Life

A day in the life at Flatiron School Houston

Every day is unique at Flatiron School, and our curriculum team and instructors develop new lessons that build off past experiences. But structured, consistent learning is also crucial to student success. Below is what you can expect on a daily basis in a Flatiron classroom.

9 a.m.

Student-Led Discussion

Students’ questions start a morning conversation, used to review new skills and program materials from the day before to ensure each student is up to speed.

10 a.m.

Lecture

Students learn key concepts from their expert instructor through interactive exercises and collaborative discussion.

1 p.m.

Pair-Programming Exercises

Two students will work together to build statistical analyses and robust coding strategies.

4 p.m.

Labs & Mini Projects

Students will apply lessons learned from lecture to solve real business problems — take messy data, clean it, and gain actionable insights from the numbers.

6 p.m.

Homework

Students end the day reviewing concepts and strategizing the next steps in their personal projects.

Learn from seasoned data scientists in Houston

Since day one over five years ago, we’ve taken teaching seriously. Great teachers inspire us to connect to topics on a profound level. With experience both in the field and in the classroom, our data science instructors are dedicated to your data science training. Simply put: students learn from the best at Flatiron School.

  • Lore Dirick

    Lore Dirick

    Curriculum Writer

    Lore earned her PhD in Business Economics and Statistics at KU Leuven, Belgium and has a thorough background building out R and Python data science curriculum.

  • Mike Kane

    Mike Kane

    Curriculum Writer

    A long-time instructor, Mike has taught Data Science on both coasts and developed curriculum for Machine Learning and iOS Development.

  • Alison Peebles

    Alison Peebles

    Lead Instructor

    Alison has private and public sector experience as a statistician, consultant, and Data Scientist. She’s taught data mining and built curriculum at Carnegie Mellon for the Masters of Science in Information Technology students.

Learn from full-time, seasoned, passionate instructors who teach students both the hard and soft skills they need to change their lives.

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Land a data science job offer in Houston with the help of our Career Services team
Career Services

Land a data science job offer in Houston with the help of our Career Services team

According to LinkedIn as of December 2018, there are about one thousand data scientist opportunities available in Houston. Thankfully, with over five years of working with passionate students and helping them launch fulfilling careers in tech, we’ve developed a keen understanding of what goes into getting that first data scientist job – both on our end and what you’re empowered to do on yours.

Individual Career Coaching

During the job-search phase, students meet with a dedicated coach every week, to ensure an effective job search via resume review, mock interviews, and developing the right job-search collateral to tell their story.

Job-Search Framework

At Flatiron School, you won’t just learn to code. You’ll also learn how to be an effective job seeker and no-brainer tech hire. Through one-on-one guidance from our Career Services team and our tried-and-true job search framework, you’ll launch your career in code far beyond the bootcamp.

Vast Employer Network

For over six years, our Employer Partnerships team has been developing relationships with hiring partners across the country to help Flatiron School grads get in the door. Our dedicated Employer Partnerships team is the best in the industry — constantly evangelizing for our graduates at companies across the world.

Money-Back Guarantee

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 details.)


The Houston Tech Scene & Flatiron's Grads

After graduation, our students have impacted powerful change and made contributions at a multitude of companies. Here in Houston, which is quickly growing as one of the country’s most innovative and promising tech hubs, we’re looking forward to doing the same.

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Tuition, Start Dates & Admission

Find the right tuition plan for you

Loan
Finance for as low as
$
380/month

Dedicated to making our programs more accessible, we offer competitive financing options through Skills Fund and Climb, two industry-leading accelerated learning financing companies.

Pay Upfront
Full Tuition
$
15,000

Scholarships

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.

What the application process looks like
Admissions

What the application process looks like

Our school brings together people who see data science as a craft, and want to be great at it. Our students come from myriad backgrounds and previous career paths — insuring that a diversity of thought, experience, and perspective are not only invited, but actively sought. At Flatiron School, all you need is passion and an open mind.

Step 1 → Apply

Apply to the course. Tells us about yourself and why you want to start a career in code.

Step 2 → Admissions Interview

Speak with a member of the Admissions team about your interests and ambitions. There is no technical preparation for this one.

Step 3 → Technical Review

The technical review assesses your basic grip of coding and how it interacts with us daily. Showing proactiveness by completing steps on Learn, our learning platform, also helps.

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Step 4 → Admissions Decision

Receive your acceptance decision from Admissions. This usually happens within a couple of days, and would be your final step!

Program dates

FAQ

You have questions; we have answers

  • How can I apply to scholarships for the in-person program?

    All scholarships to our in-person program are granted after a student is admitted. Scholarships are granted on a need and merit basis, with preference given to underrepresented minorities in tech, including women and military veterans. If you feel that describes you, you can share your story with us on the scholarship application once you are admitted into the program.

  • I was admitted to a cohort but can’t start until next month, can I defer my enrollment?

    We recognize that sometimes “life happens” and that students who have been admitted to one class may need to defer and start with us at a later date. Students may defer up to three start dates beyond the class to which they are admitted. If you must defer farther out than that, we may ask you to repeat some or all of the admissions process to ensure your readiness for the later start date. Students may defer only once without reapplying.

  • I wasn’t admitted the first time around, can I re-apply?

    Flatiron School’s application process is rigorous, and sometimes students who don’t get accepted the first time around are able to ‘study up’ and get accepted the second time around. As such, students are invited to re-apply after three months have passed from initial decision. Students are permitted a total of three application attempts, so re-applicants are advised to use that time building their skills (both professional and technical) and to submit a second application that is materially different from the first one, showcasing your hard work and improvements over that time.

  • Is there a deadline by which to apply?

    Admissions are conducted on a rolling basis, so we continue to accept new applications until the course is filled. Therefore, there is no deadline to apply by – though the sooner you get your application in, the better we are able to prioritize it. Because our classes fill up well in advance of the start date, we recommend applying at least 8 weeks before your desired course date. This allows us 2-3 weeks to conduct the application process and accounts for time to complete the mandatory 100 hours of pre-work, which most students report takes at least 3 weeks.

Additional FAQs

Apply Today and Learn to Change Your Career

Start your application for Flatiron School Houston's immersive Data Science course and change your life today.

Visit Our Campus or Attend an Event

Join us for a campuss tour, seminar, or info session to see what student life is like on our vibrant campuses.

Schedule a Q&A with Admissions

Have a question about our program that we haven’t answered above? Our admissions team is here to help.