FRONT-END
WEB DEVELOPMENT

LEARN IN-DEMAND CODING SKILLS FROM EXPERT DEVELOPERS IN OUR 10-WEEK, PART-TIME COURSE.

Get Ahead With Today’s Essential Skills

Learn to leverage HTML, CSS, and JavaScript through hands-on projects and real-world scenarios. Develop interactive, responsive websites to impress new clients and employers with your coding skills and get ahead on the job.

Evolve With the Tech-Driven Economy

Tap into the universal demand for coding skills, and reach new heights in your career. Our dynamic coursework is designed by industry experts and continuously updated to meet today’s employer demands.

Become Part of a Global Community

Collaborate with expert developers and peers at the local level, and join GA’s growing global network. After graduation, you’ll access exclusive perks, opportunities, and events to continue pursuing a lifetime of learning.

SEE WHAT YOU’LL LEARN

Can I visit the Manhattan campus?

We offer tours and info sessions on a regular basis, and you can register on our community page. If our event times don’t work for you, please email admissions@flatironschool.com to schedule an appointment at an alternative time.

Can I apply for financing?

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.

Can I chat with someone on the Admissions team?

Absolutely! You can schedule an appointment with someone from the Admissions team.

Do I need a computer?

For the in-person courses, we work on Mac laptops with the latest OS installed. If you don’t have one already, we can provide a loaner. For online courses, you do need your own computer, but it can be either a Macbook or a PC. You can view the minimum required technical computer specs for all courses.

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?

Codeva 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 to apply?

Admissions are conducted on a rolling basis, so we continue to accept new applications until the course is filled. So, no deadline to apply — but the sooner you get your application in, the faster we can prioritize it. Our classes fill up well in advance of the start date, so we recommend applying at least 8 weeks before your desired start date. This allows 2–3 weeks for the application process and accounts for time to complete the required 100 hours of pre-work.

MEET YOUR SUPPORT TEAM

 

Our educational excellence is a community effort. When you learn at GA, you can always rely on an in-house team of experts to provide guidance and support, whenever you need it.

Instructors

Learn industry-grade frameworks, tools, vocabulary, and best practices from a teacher whose daily work involves using them expertly.

Teaching Assistants

Taking on new material isn’t always easy. Through office hours and other channels, our TAs are here to provide you with answers, tips, and more.

Become Part of a Global Community

Taking on new material isn’t always easy. Through office hours and other channels, our TAs are here to provide you with answers, tips, and more.

EXPLORE STUDENT WORK

 

Our student project gallery showcases work by alumni of this course. Take a look — and imagine what you could make possible.

A Light Year

by Debra Ohayon

An interactive visualiziation how far light travels in a year.

C.Ville Coffee

by Katie Cullinan

A website for a coffee shop in the DC metro area.

Put A Bird On It

by Clayton Hopkins

A responsive website with a game, inspired by a favorite show.

What you’ll learn: data science & machine learning

 

From Python to Machine Learning, our 15-week data science training program gives you the breadth and depth needed to become a well-rounded data scientist. You’ll  also leave with an understanding of how to discover new techniques as your career progresses.

Every 3 weeks you’ll be introduced to a new module that builds off the learnings of the previous section while allowing you enough time to dive into each area for a thorough understanding of the subject matter.

Prework Modules

The 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 you come in prepared and are 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. To organize your data, you’ll learn about data structures, relational databases, ways to retrieve data, and the fundamentals of SQL for data querying for structured databases. Furthermore, you’ll learn how to access data from various sources using APls, as well as perform Web Scraping.

Finally, we’ll conclude with a heavy focus on visualizations as a way to go from data to insights.

At the end of this module, students will use their newly learned skills to collect, organize and visualize data, with the goal to provide actionable insights!

Module 1 Topics

Variables, Booleans and Conditionals, Lists, Dictionaries, Looping, Functions, Data Structures, Data Cleaning, Pandas, NumPy, Matplotlib/Seaborn for Data Visualization, Git/Github, SQL, Accessing Data Through APIs, Web Scraping

Having learned how to gather and explore data with Python and SQL you can now go deeper into analyzing that information with statistics. In this module, you’ll learn about the fundamentals of probability theory, where you will learn about probability principles such as combinations and permutations. You will go on and learn about statistical distributions and how to create samples when distributions are known. By the end of this module, you will be able to apply this knowledge by running A/B tests. Additionally, you’ll learn how to build your first (and important) data science model: a linear regression model.

Module 2 Topics

Combinatorics, Probability Theory, Statistical Distributions, Bayes Theorem, Sampling Methods, Hypothesis Testing, A/B Testing, Linear Regression, Model Evaluation

Module 3 is all about machine learning, with a heavy focus on supervised learning. To start, you will go a little deeper into regression analysis, learning about extensions to linear regression, and a new form of regression: logistic regression. In building regression models, students will learn about penalization terms, preventing overfitting through regularization and using cross validation to validate regression model.

Next, you’ll learn how to build and implement the most important machine learning techniques. You’ll learn about classification algorithms such as Support Vector Machines and Decision Trees. Additionally, you’ll learn how to build even more robust classifiers using ensemble methods such as Bagged and Boosted Trees, and Random Forests.

Module 3 Topics

 

Linear Algebra, Logistic Regression, Maximum Likelihood Estimation, Optimization Cost Function, Gradient Descent, K Nearest Neighbors, Decision Trees, Ensemble methods, Pipeline Building, Hyperparameter Tuning, Grid Search, Scikit-Learn

After a full module on supervised learning, this  module focuses on a variety of advanced Data Science techniques. You will start with learning about unsupervised learning techniques such as clustering techniques and dimensionality reduction techniques. Next, you will be introduced to threading and multiprocessing to be able to work with big data.  In doing so, you’ll learn about PySpark and AWS, and how to use those tools to build a recommendation system. Next, you will get an in-depth overview of deep learning techniques, learning about densely connected neural networks, enabling high-performing classification performance. Next, students will learn how to use regular expressions in Python, and how to manage string values, analyze text and perform sentiment analysis.

Module 4 Topics

Dimensionality Reduction, Clustering, Time Series Analysis, Neural Networks, Big Data, Natural Language Processing, Text Vectorization, Natural Language Toolkit, Regular Expressions, Word2Vec, Text Classification, Recommendation Systems

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 course’s time constraints. At the end of the project, you’ll receive a grade based on various factors.

Upon project completion, you’ll know 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.

Module 5 Topics

Final Project

Join the fastest-growing corner of the tech industry

 

More than ever before, companies are relying on data to make business decisions. Without data science, these industry trends stay undiscovered — no story to tell and no insights to share. In order to determine business goals, more and more companies are looking for data scientists to fill in the gaps. Data science is one of the fastest-growing and sectors of the tech industry.

650%

Growth in Data Science Jobs Since 2012

The course will qualify you for a position as a data scientist or a data analyst. If you have a professional background in programming, you may also be able to get a position as a data engineer or a machine learning engineer.

Meet your teachers

 

At Codeva, we believe that great teachers help us understand topics on a profound level and inspire us to become continual learners. With experience in the field and in the classroom, our data science instructors are dedicated and thorough. Simply put: you learn from the best.

Sean Abu Wilson

Lead Instructor

Sean Abu joined Codeva after working for IBM as a Data Scientist Consultant and as a high school economics teacher. As a lead instructor, he combines his past experiences to prepare students for their future.

David John Baker

Lead Instructor

David John Baker, PhD is a data scientist and educator passionate about all things related to music, theory, and science. He’s applied his data science skill set in academic, industry, and charity settings and currently serves as a lead instructor

Fangfang Lee

Lead Instructor

After earning a Masters in Statistics from New York University, Fangfang worked as a data scientist in the public policy and start-up sectors. However, her love of teaching led her to join Flatiron School as a lead instructor

Navigate tech’s top opportunities with the help of our Career Services team

 

At Codeva, you won’t just learn data science. You’ll also learn “How to be a No-Brainer Tech Hire” and effective job seeker. With 1-on-1 career coaching, a robust employer network, and a proven job search framework, our Career Services team is committed to helping you launch a career in tech.  

Individual career coaching

During your job search, you’ll meet weekly with your dedicated Career Coach. Coaches help with everything from résumé review to interview prep, and help you tell your story to land your first job.

Money-back guarantee

Change careers with confidence thanks to our Money-Back Guarantee. If you graduate, follow our job-search process, and don’t secure a job offer within 6 months, we’ll refund your tuition in full (see details).

Vast Empoyer Network

We’ve built relationships with hiring managers at top companies across the world, creating a robust employer pipeline for Flatiron School grads. Our Employer Partnerships team is constantly advocating for our grads and helping you get in the door.

Proven job-search framework

Through 1-on-1 guidance from our Career Coaching team and our tried-and-true job-search framework, you’ll gain the skills and support you need to launch your career.

Join us on campus

Cohort Start Date Status
Feb 17, 2020  May 29, 2020 Closing Soon  Apply Now
Mar 30, 2020  Jul 10, 2020 Open  Apply Now
May 11, 2020  Aug 21, 2020 Open  Apply Now
Jun 22, 2020  Oct 2, 2020 Open  Apply Now
Aug 3, 2020  Nov 13, 2020 Open  Apply Now

Take the leap and start your journey

 

Codeva curates a community by admitting students who bring creativity, ingenuity, and curiosity to the classroom.

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Step 1 → Apply

Submit your application. Share a bit about yourself and what’s driving you to start a career.

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Step 2 → Admissions interview

Speak 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.

Step 3 → Technical review

After writing and submitting some code on Learn.co, you’ll attend a live interview session with an instructor to assess your understanding of the material.

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Step 4 → Admissions decision

Receive your acceptance decision from Admissions. This usually happens within 4 business days.

Step 5 → Prework

If accepted, you’ll begin course pre-work to prepare for the first day of class.

Find the right tuition plan for you

Loan

Finance for as low as

380/mo

 

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

Loan

Full Tuition

17,000

ISA

Deferred Tuition

Defer your tuition with the Flatiron School Income Share Agreement (ISA). After a refundable payment when you enroll, the remainder of your tuition is paid once you’ve left the program and are getting paid at least a minimum income.

Frequently asked questions

Can I visit the Manhattan campus?

We offer tours and info sessions on a regular basis, and you can register on our community page. If our event times don’t work for you, please email admissions@flatironschool.com to schedule an appointment at an alternative time.

Can I apply for financing?

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.

Can I chat with someone on the Admissions team?

Absolutely! You can schedule an appointment with someone from the Admissions team.

Do I need a computer?

For the in-person courses, we work on Mac laptops with the latest OS installed. If you don’t have one already, we can provide a loaner. For online courses, you do need your own computer, but it can be either a Macbook or a PC. You can view the minimum required technical computer specs for all courses.

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?

Codeva 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 to apply?

Admissions are conducted on a rolling basis, so we continue to accept new applications until the course is filled. So, no deadline to apply — but the sooner you get your application in, the faster we can prioritize it. Our classes fill up well in advance of the start date, so we recommend applying at least 8 weeks before your desired start date. This allows 2–3 weeks for the application process and accounts for time to complete the required 100 hours of pre-work.

Change Your Career

Start your application and change your life today.

Attend an Event

Join us for a seminar or info session to see what student life is like at Flatiron School.

Chat with Admissions

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

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