Data Science & Engineering Bootcamp
Bridge the gap in big data with the Data Science & Engineering Program.
Do you have what it takes to bridge the gap into data engineering?
Our Data Science & Engineering Bootcamp isn’t your ordinary data program—it’s immersive. Our live instruction means you’ll work with industry-specific tools, current datasets and our experienced instructors will help you master the data skills you need to succeed in the growing field of data science and engineering.
There’s a reason why we’re one of the leading data training and placement organizations in the world—our tried-and-true curriculum is tailored to ensure students graduate as well-rounded data professionals and this program is no exception.
The Data Science & Engineering Program
The Data Science & Engineering Bootcamp is designed to bridge the gap between data science and data engineering. You’ll master the skills needed to design better data models, build data infrastructures, automate data pipelines, maintain data architecture and effortlessly work with massive datasets.
This program is ideal for those with a computer science or software engineering background who have a passion for improving productivity with data and enjoy the challenge of the constantly evolving sources of semi-structured data. You’ll learn the crucial skills of building the sophisticated platforms that businesses desperately need to organize their data teams.
In addition to great skills training, you’ll work on a capstone portfolio to showcase your knowledge and talent to future employers.
Your Future Awaits
Who's it for?
- Are a full-time student looking to expand your computer science and data knowledge
- Are a recent Master’s or PhD graduate with a strong background in computer or data science (ie: web development, software engineering, etc.)
- Are an individual with a Bachelor’s with a robust understanding of the computer sciences looking to break into a data profession
- Need help finding a lifelong career in a growing field with endless opportunities
Then this course is for you.
What Does it Cost?
Tuition for the Data Science & Engineering Bootcamp is $10,000.
We are proud to offer a number of full-tuition scholarships for this program. To be considered for one of our limited tuition-free spots, all you have to do is apply! We select recipients from those we believe to be the most qualified.
Looking for financing information? Check out our options here.
Get Career Support Until You're Hired
In addition to the in-demand skills and programs you’ll learn, you’ll have the opportunity to work with a career coach to craft the perfect resume and hone your interview skills so you can shine in front of potential employers.
Build a network of fellow data engineers and broaden your connections so you can find the right role for you. Nearly 80% of jobs are found through your network, according to LinkedIn, and we’ll help you expand your world.
More About the Data Science & Engineering Bootcamp
Our immersive, hands-on data engineering program for those with a passion for bridging big data gaps and maintaining data architecture.
You’ll work on projects that showcase your world-class data engineering skills using complex datasets to solve the increasing gap in businesses data teams. Choose the data that sparks your interest and build a platform that shows off your mastery of data engineering to future employers with a capstone portfolio.
To help you find your first—or next—job as a data engineer, we include a robust career services program.
If you’re interested in our limited, tuition-free fellowship spots, you only need to complete the application. We select recipients from those we believe to be the most qualified.
Sneak-Peek of the Data Science & Engineering Curriculum
Database systems (SQL and NoSQL). Data engineers must know how to manipulate database management systems (DBMS), which is a software application that provides an interface to databases for information storage and retrieval.
Data warehousing solutions. Data warehouses store huge volumes of current and historical data for query and analysis. Most employers expect entry-level engineers to be familiar with a cloud services platform (Amazon Web Services) that provides a whole ecosystem of data storage tools.
ETL tools. ETL (Extract, Transfer, Load) pulls data from various sources, applies certain rules to the data according to business requirements, and then loads the transformed data into a database or business intelligence platform so it can be used and viewed by anyone in the organization.
Machine learning. Machine learning algorithms help data scientists make predictions based on current and historical data. Data engineers only need a basic knowledge of machine learning as it enables them to understand a data scientist’s needs better, get models into production and build more accurate data pipelines.
Data APIs. An API is an interface used by software applications to access data. It allows two applications or machines to communicate with each other for a specified task. Data engineers build APIs in databases to enable data scientists and business intelligence analysts to query the data.
Understanding the basics of distributed systems. Hadoop fluency is one of the most important data engineer skills. Apache Spark is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. Apache Spark is the most widely used programming tool in data science and Data Engineering.
Knowledge of algorithms and data structures. Data engineers focus mostly on data filtering and data optimization, but a basic knowledge of algorithms is helpful for understanding the big picture of the organization’s overall data function, as well as define checkpoints and end goals for the business problem at hand.
Get the skills you need to achieve your career goals.
Over the course of our program, you’ll master the most in-demand skills, including:
Career Services with The Data Incubator
Our career services team will work with you and our pool of hiring partners to find you amazing opportunities you won’t see anywhere else. You could be working an exciting new career in a matter of months for a leading company like:
What does it take to become a TDI-certified data engineer?
We’ll ask you all the usual questions about your education and work experience and other details that help us determine if you meet the basic qualifications for the program.
You must have at least one of the following:
- A Master’s degree completed before the program begins
- A PhD degree completed before the program begins
- A PhD degree that will be completed within 3 months of the conclusion of the program
- A Bachelor’s degree and extensive experience in a data-related position
We highly encourage you to apply by the early decision date. We view applications on a first come, first served basis, and the sooner you get yours in, the better chance you have of moving forward and earning money off your tuition.
Once you’ve completed your application, you’ll move into the interview.
After you apply, we’ll contact the most promising candidates to set up a time for an online interview with our instructors and staff.
If you are advanced to the next and final round, you will be invited to complete a technical assessment/coding challenge.
Those who show the most promise during the entire application process are awarded one of our limited tuition-free spots, so put your best foot forward. Tell us why you think you’re the right candidate for the program.
Check out this handy infographic to get some of our best tips and tricks for doing well during your interview.
Tuition-free spots are limited, but that’s not the only way to attend our program. We now offer income-sharing agreements, which allow you to pay your tuition after you’ve secured a job and are earning more than $40,000 per year. Check out the details.
This coding challenge is designed for you to show off your current abilities. You’ll get 72 hours to complete the challenge once you start, so make sure you’re prepared to give it your all. The challenge will close for all applicants after the application closes regardless of the time you have left.
Keep in mind: You don’t have to finish all of the challenges, but you do need to do as much as you can. We look at the quality of your work as well as the quantity. And make sure you save as you go. You can come back and continue your work during those 72 hours, but the last time you save is the version we’ll look at.