Immersive Data Science Bootcamp

Online Info Session + Rshiny Demo Lesson

Wednesday, January 16th, 2019   |  7 PM EST

Sign up for info session

Considering a switch to the Data Science profession?

Join our live online info session about how to start a career in data science! 

This event is to help you with important information regarding NYCDSA and how it has assisted many in achieving their data science goals at companies such as Facebook, Spotify, Google, JP Morgan, and more! We know what it takes to succeed in this field.  

Throughout the session, you'll learn the tools, techniques, and fundamental concepts you need to know to make immediate impacts with data.
We will do a course overview and expected outcomes, and cover the admission process as well as career services.

What you will learn from this session:

In the first part of the info session, we will give you an overview of what makes NYC Data Science Academy different. You will learn how to prepare for the bootcamp, what to learn, and application process. 

The second part of the information will be a demo session given by Data Science instructor David Romoff. David is a risk management consultant with 10 years of experience modeling market and credit risk using the latest methods and technologies. David's recent work includes serving as Manager of Risk Management at On Deck Capital, a business lending company in the FinTech space that uses machine learning models to underwrite loans.  He has an MBA from the Zicklin School of Business in New York City and a Master of Science in Actuarial Science from Columbia University. 

The workshop is not meant to give a mathematics overview of machine learning models. Students are not required to have coding to attend. A laptop with a working installation of R version > 3.30 is recommended.

The information session will be as follows: 

  • 6:45 - 7:00 pm - Check-in, meet, and greet
  • 7:00 - 7:10 pm - Introduction to NYC Data Science Academy and What We Do
  • 7:10 - 7:45 pm - Demo Lesson
  • 7:45 - 8:00 pm - Questions from participants

 

Look forward to seeing you online

Wednesday, January 16th, 7 PM EST