Data Scientist: The Sexiest JobHarvard Business Review
of the 21st Century
The Data Incubator's Foundations of Data Science online training course is an introductory 8-week, part-time bootcamp geared towards giving ambitious college and graduate-level students, recent college graduates, and working professionals an immersive hands-on experience with foundational data science techniques. Class sessions are LIVE online presentations, twice each week for two hours each session. Our Foundations of Data Science online training course curriculum has been developed with feedback from our hundreds of industry partners, using the same rigorous methodology as our Fellowship program, to transform data amateurs into data professionals.
Learn from The Data Incubator's experienced data science instructors dedicated to teaching data analytics.
Learn the most sought-after tools and techniques in the industry to help jumpstart your data analyst career.
This course was designed for the busy lives of working professionals with a part-time schedule and recorded lectures.
Gain hands-on experience applying the tools employers value to real-world datasets. All powered by a 100-node cluster.
Live lectures allow you to ask your instructor questions and interact with your classmates.
Small class sizes ensure you have plenty of access to your instructor and can receive personalized feedback on your progress.
The next Foundations course will run from 2018-04-10 to 2018-05-31. Classes are generally held on Tuesdays and Thursdays from 7-9 PM Eastern, with some exceptions for holidays. The deadline for registration is 2018-03-30. The course tuition is $3,495.00 with early-bird discounts available.
The exact dates for the next session will be: 4/10, 4/12, 4/17, 4/19, 4/24, 4/26, 5/1, 5/3, 5/8, 5/10, 5/15, 5/17, 5/22, 5/24, 5/29, 5/31
Interested in the course but need help with financing? We've partnered with Climb Credit to help. Climb offers affordable, 3-year financing with fixed interest rates and low monthly payments. Apply online and get a decision same-day with no impact on your credit. Have questions about how it works? Check out their FAQ.
Dylan Bargteil studied physics and math at University of Maryland, and received a PhD in physics from New York University. At University of Maryland he was a research and teaching assistant developing new introductory physics curriculum and pedagogy in partnership with HHMI. Prior to joining The Data Incubator as a Data Scientist in Residence, he worked with deep learning models to assist surgical robots. At The Data Incubator he continues his research-guided curriculum development and instruction.View resume (pdf)
"The data science skills I sharpened at The Data Incubator helped me analyze diversity in STEM education, model SaaS stock prices, and compare industry growth rates. The instructor's background in quantitative finance made for relevant use cases that benefit not only data scientists, but also data-driven finance people like myself."
"From day one I was getting my hands dirty working with data using industry-relevant tools. Having completed the program I'm now better equipped to manage engineering and product teams, and able to conduct sophisticated ad-hoc analysis. Everyone at TDI blew me away; truly exceptional."
"Their heavy focus on applied learning meant that I was working on real data and solving real problems right from the start. While lectures were a valuable component of their courses, the real learning took place while working on projects. These projects were practical, engaging, and instructive, and generally great opportunities to get hands-on experience with what I had learned in the lectures."
This course is designed for anyone who would like to learn the essentials of data science. Students will gain hands-on experience working with some of the most in-demand big data technologies and leave ready to kickstart their data science careers.
You can find the dates of upcoming sessions and register via The Data Incubator's Eventbrite page.
Our Foundations course includes four hours of lectures each week. You'll also want to allot extra time for reviewing lectures and working on the associated projects; we generally recommend setting aside at least four additional hours per week for this, but it's up to you how much time you'd like to put in.
As Foundations is intended to add a set of skills for students who are currently employed full time, we do not offer placement or job search support for this course.
The Foundations course was initially designed as a prep course for students applying to our Data Science Fellowship, and builds skill sets in two areas essential to the Fellowship: the ability to code proficiently in Python and the ability to apply statistical methodology to datasets. However, completion of the Foundations course does not guarantee acceptance into the Fellowship program.
The Data Incubator's Fellowship program is a full-time, intensive data science program spanning two months. Fellows in the program should have programming experience, a background in a highly analytical field, and the ability to work independently on programming projects. This course is for people with advanced degrees who want to make a full transition from academia to industry-focused data science.
The Foundations course, on the other hand, is a part-time, online program designed for people who'd like to learn the essentials of data science to augment their current skill sets. The class is centered on data wrangling and analysis using Python and is taught by a live instructor. Prior coding experience is definitely a plus, but not required (see next section).
There's no official skill set required for this course, but a basic understanding of the Python language is strongly encouraged. If you don't have any experience with Python, we recommend you complete Codecademy's free Python basics courses before beginning the Foundations program. With that said, we've had successful students in the past who came to us with no prior coding experience.
Foundations students will learn how to programmatically work with large, real-world datasets to solve business problems. Over the course of eight weeks, students learn how to extract, clean, and analyze data using Python. Students will leverage Python's powerful libraries to build predictive models to make better decisions, and help employers solve business problems using data-driven insights.
Yes! Thanks to a new partnership with Climb Credit, Foundations students can apply for an affordable, fixed-interest financing plan with low monthly payments. You can submit your application online and get a decision the same day, with no impact to your credit score. If you're interested in applying, you can find more information here.
With loads of data you will find relationships that aren’t real.Forbes Magazine
Big data isn’t about bits,
it’s about talent.