9780578973838-0578973839-Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street

Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street

ISBN-13: 9780578973838
ISBN-10: 0578973839
Author: Nick Singh, Kevin Huo
Publication date: 2021
Publisher: Ace the Data Science Interview
Format: Paperback 301 pages
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Book details

ISBN-13: 9780578973838
ISBN-10: 0578973839
Author: Nick Singh, Kevin Huo
Publication date: 2021
Publisher: Ace the Data Science Interview
Format: Paperback 301 pages

Summary

Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street (ISBN-13: 9780578973838 and ISBN-10: 0578973839), written by authors Nick Singh, Kevin Huo, was published by Ace the Data Science Interview in 2021. With an overall rating of 4.2 stars, it's a notable title among other AI & Machine Learning (Data Modeling & Design, Databases & Big Data, Data Mining, Data Processing, Mathematical & Statistical, Software, Computer Science) books. You can easily purchase or rent Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street (Paperback) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $12.99.

Description

Authored by two Ex-Facebook employees,
Ace the Data Science Interview is the best way to prepare for Data Science, Data Analyst, and Machine Learning interviews, so that you can land your dream job at FAANG, tech startups, or Wall Street.
What's inside this 301 page book?
201 real Data Science interview questions asked by Facebook, Google, Amazon, Netflix, Stripe, Two Sigma, Citadel and more — with detailed step-by-step solutions!
Questions cover the most frequently-tested topics in data interviews: Probability, Statistics, Machine Learning, SQL & Database Design, Coding (Python), Product Analytics, and A/B Testing
Each chapter has a brief crash-course on the most important concepts and formulas to review
Learn how to solve open-ended case study questions that combine product-sense, business intuition, and statistical modelling skills, and practice with case interviews from Airbnb, Instagram, & Accenture
Learn how to break into Data Science, with tips on crafting your resume, creating kick-ass portfolio projects, sending networking cold emails, and better telling your story during behavioral interviews
Praise for Ace the Data Science Interview:
"The advice in this book directly helped me land my dream job"
— Advitya Gemawat, ML Engineer, Microsoft
“FINALLY! Cracking the Coding Interview but for Data Science & ML!”
— Jack Morris, AI Resident, Google
"Super helpful career advice on breaking into data & landing your first job in the field"
— Prithika Hariharan, President of Waterloo Data Science Club; Data Science Intern, Wish
“An invaluable resource for the Data Science & ML community”
— Aishwarya Srinivasan, AI & ML Innovation Leader, IBM
“Solving the 201 interview questions is helpful for people in ALL industries, not just tech!”
— Lars Hulstaert, Senior Data Scientist, Johnson & Johnson
“The authors explain exactly what hiring managers look for — a must read for any data job seeker”
— Michelle Scarbrough, Former Data Analytics Manager, F500 Co.About Kevin Huo:
Kevin Huo is currently a Data Scientist at a Hedge Fund, and previously was a Data Scientist at Facebook working on Facebook Groups. He holds a degree in Computer Science from the University of Pennsylvania and a degree in Business from Wharton. In college he interned at Facebook, Bloomberg, and on Wall Street. About Nick Singh:Nick Singh started his career as a Software Engineer on Facebook's Growth Team, and most recently, worked at SafeGraph, a geospatial analytics startup. He holds a degree in Systems Engineering with a minor in Computer Science from the University of Virginia. In college, he interned at Microsoft and Google. His career advice has been read by over 10 million people on LinkedIn.

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