Data Scientist: The Sexiest JobHarvard Business Review
of the 21st Century
The Data Incubator is a Cornell-funded data science training organization. We run an introductory 8-week part-time online program geared towards giving working professionals an immersive hands-on experience with Machine Learning. Developed based on feedback from our hundreds of industry partners and using the same rigorous methodology as our Fellowship, the curriculum transforms ML amateurs into ML 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.
This class is for you if:
Upon completion of this course, you will:
The next Machine Learning course will run from 2018-07-09 to 2018-08-29. Classes are generally held on Mondays and Wednesdays from 7-9 PM Eastern, with some exceptions for holidays. The deadline for registration is 2018-06-22. The course tuition is $3,495.00 with early-bird discounts available.
The exact dates for the next session will be: 7/9, 7/11, 7/16, 7/18, 7/23, 7/25, 7/30, 8/1, 8/6, 8/8, 8/13, 8/15, 8/20, 8/22, 8/27, 8/29
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.
"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."
With loads of data you will find relationships that aren’t real.Forbes Magazine
Big data isn’t about bits,
it’s about talent.