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Introduction to Data Science and Analysis


Thomson Nguyen
Founder/CEO, Framed Data

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About This Class

Everyone's talking about them, and yet no one has reached a consensus on what exactly they do--it seems like despite their black-box processes and amorphous job descriptions, data scientists are here to stay.

This class is designed to give newcomers some clarity into how data scientists add value to any organization, the tools and skill set required to succeed as one, and a sample case study on how data science is uniquely positioned to solve some of the coolest company problems. By the time you finish this class, you'll have a better idea of what the field is and more importantly, how you can help yourself become what the Harvard Business Review calls the "sexiest job of the 21st century".


  • Introduction 1:56
  • The Data Pyramid 11:15
  • How to Be a Data Scientist 3:01
  • What Makes a Good Model 5:58
  • The Data Science Work Flow 5:33
  • Case Study 11:46
  • Q&A 10:20


  • An introduction to a standard workflow for anyone conducting data analysis (using Ben Fry's process),
  • Knowledge and sample R code from a specific data-related case study we'll cover together, and
  • Tools and resources to help you find answers to questions that may come up in future analyses.

Prereqs & Preparation

Beginner/Intermediate. This is a general survey of how you can add value as a data analyst/scientist rapidly in any organization. As a result, we'll cover a lot of things and only drill-down on one specific case study. This class is best for people who need an introduction to data analysis and data science techniques, or people who are looking to switch into a data-related position.

About the Instructor(s)


Thomson Nguyen
Framed Data

Thomson Nguyen is a co-founder and CEO at Framed Data, where he works on various data problems in analytics, infrastructure, and machine learning for businesses and non-profits. He is also a visiting scholar at the Courant Institute for Mathematical Sciences at NYU, where his research interests lie in malicious malware behavior and parallelized decision trees. He is currently writing a book on common but useful data science recipes for startups, and is also re-learning Spanish (slowly). He studied Mathematics at the University of California, Berkeley, and Computational Biology at the University of Cambridge. He loves good iced coffee, rowing, and reuben sandwiches.

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