Skip to content

Resources for Oreilly's "Cracking the Data Science Interview" video series.

Notifications You must be signed in to change notification settings

ibelieveai/cracking-the-data-science-interview

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Cracking the Data Science Interview

This repository contains resources to prepare for a data science interview, as well as resources to navigate the interview process. These resources were created to supplement the O'Reilly video course: Cracking the Data Science Interview.

Materials

What is in Here

This repository contains the following files:

Video Series

The corresponding videos can be found on the following sites for purchase:

  • [O'Reilly site (individual purchase)][0]
  • [Safari Books Online (subscription)][0.1]

Contact

And/or please do not hesitate to reach out to me directly via email at jondinu@gmail.com or over twitter @clearspandex

If you would like to contribute, please fork this repository and submit a pull request

What You Will Learn

  • How to prepare for a data science interview
    • Am I ready to Apply?
    • Necessary theory background
    • Necessary coding background
    • The data science interview process
    • What role is best for me
  • Getting Interviews
    • The interview funnel
    • Better application techniques
    • Crafting your pitch
    • Reaching out and sourcing contacts
  • Journey of an Alumnus (of the Galvanize Data Science program)
  • Mock interviews
  • Negotiation for Data Scientists
    • Knowing what you are worth
    • Negotiation strategies 101
    • How to evaluate offers

Who Should Watch the Videos

  • Aspiring Data Scientists who are eager to learn what skills they need to begin applying to data science jobs.
  • Experienced Data scientists who already feel they have the requisite theory and coding background and want a structured approach to applying for their next job.

About

Resources for Oreilly's "Cracking the Data Science Interview" video series.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published