WARNING FOR U.S. CUSTOMERS: Counterfeit & pirated books filled with mathematical typos, missing pages, and poor print quality are being sold by 3rd-party Amazon sellers as "USED - LIKE NEW" or "USED - VERY GOOD" condition books. Do NOT buy used from 3rd party Amazon sellers like 'Be_YOU_tiful', 'BuyFromFellowStudent', 'Pampered Diva', etc. To ensure a genuine copy, BUY THE BOOK NEW and make sure it says "Ships From & Sold by Amazon.com" (this is usually the default 'New' buying option). 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, Two Sigma, Citadel and more — with detailed step-by-step solutions!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 interviewsQuestions cover the most frequently-tested topics in data interviews: Probability, Statistics, Machine Learning, SQL & Database Design, Coding (Python), Product Analytics, and A/B TestingEach chapter has a brief crash-course on the most important concepts and formulas to reviewLearn how to solve open-ended case study questions that combine product-sense, business intuition, and statistical modeling skills, and practice with case interviews from Airbnb, Instagram, & AccenturePraise 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 on LinkedIn has garnered over 25 million views.
✔ Author(s): Nick Singh,Kevin Huo
✔ Title: Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street
✔ Rating : 4.5 out of 5 base on (877 reviews)
✔ ISBN-10: 0578973839
✔ ISBN-13: 9780578973838
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle
Readers' opinions about Ace the Data Science Interview by Nick Singh
Tasha Cobbett
This book completely captured my heart. The characters were so relatable, and their journeys resonated deeply with me. The writing was poetic and powerful, leaving me with a sense of awe. I'm grateful to have experienced this literary gem.
Laura Hill
This book is a treasure trove of knowledge and wisdom. The insights offered by the characters and their experiences have left a lasting impression on me.
Violet Tyler
This book is a work of art. The language, the imagery, the symbolism - everything came together beautifully to create a memorable reading experience.
