For tech professionals, data science is one of the most lucrative and desired career paths. It has a big impact on how businesses run and provides a lot of opportunities for growth and professional development.
Going through this list of the best data science books should undoubtedly be included in your preparation for a data science interview if you are getting ready for one soon. At the top tech companies, getting through the data science interview is by no means an easy task. You can ace your subsequent data science interview and get the job of your dreams if you have a solid plan in place.
Enrolling in a reputable resource or taking a good data science interview course can make a significant difference when preparing for an interview. We’ll talk about how books are a great way to get started with your data science interview preparation in this article. We’ll examine the top 7 data science books to assist you in preparing for your data science interview.
Check out our technical interview checklist, interview questions page, and salary negotiation e-book to prepare for technical interviews if you’re a software engineer, coding engineer, software developer, engineering manager, or tech lead.
We have trained over 10,000 software engineers, so we are aware of what it takes to succeed in even the most difficult technical interviews. Our alums consistently land offers from FAANG+ companies. The highest offer ever made to an IK alum was a mind-blowing $1. 267 Million!.
You have the exceptional chance to learn from knowledgeable instructors at IK who work as hiring managers and tech leads at leading Silicon Valley tech companies like Google, Facebook, Apple, and others.
Let’s look at the top data science books to advance your preparation for data science interviews. Reading these books will make it much simpler for you to succeed in the data science interview.
The Apple Data Science Interview
Interviews for Top Jobs at Apple
Data Scientist Interview
I applied through an employee referral. The process took 2 weeks. I interviewed at Apple (New York, NY) in Dec 2021
Interview
Internal reference and then a list of questions by email then had virtual onsite (walk through resume and then asking technical questions) After one week, their hiring decision was updated
- What machine learning courses did you take, and what concepts did you learn about penalized regression?
Data Scientist Interview
I applied online. The process took 1 day. I interviewed at Apple (Cupertino, CA) in Jun 2022
Interview
The process was simple and the questions were Easy to Medium level. I went only till the Tech Screening.I applied online and the HR contacted me.The role was focused on data analytics and not on ML or statistics at all. Not sure why they gave it DS title.
- Python: *Create a DataFrame* Return first names from a column (using str)SQL: Find rows beginning with letter “H” Tableau: * Context Filters (as well as various other filter types and uses* Dealing with Nan and null values * What should I do if a Tableau visualization takes a long time to load? Product: I’m running tests next to someone who is interfering with the power to my Mac and causing power fluctuations. You have access to a report of when the tests are run, so how can you determine if that person’s tests are to blame for the power fluctuations? Workflow for data analysis of NaNs and null values General: Have you used Splunk or Mongo DB?
The role of an Apple Data Scientist
Apple is a multinational technology company that creates, produces, and sells consumer electronics, software, and a range of online services. Apple needs data scientists who can assist its platforms in making sense of the enormous amounts of data that platforms like Siri, iCloud, and other online services continuously generate and handle.
A data scientist at Apple performs a different job than one at other companies. Apple requires what are known as full-stack data scientists, so it differs. Apple expects its data scientists to be versatile enough to work on a variety of teams, including the analytics-heavy iTunes team, the machine learning/AI-focused Siri team, the marketing and sales teams, etc.
Skills required/preferred:
The interview process at Apple is comparable to that at other significant tech firms like Facebook, Google, and Amazon. Candidates are required to submit their applications online. Those who advance to the interview round are contacted by the recruiter, who is typically the company’s HR manager. After that, candidates face a technical phone screen. Those who pass this stage of screening are invited to a lengthy on-site interview. Depending on the role, the location for the onsite interview may change. It might be located on an Apple campus in Cupertino, Austin, or another city.
100+ Interview Questions for Data Scientistsby Interview Kickstart Team in
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The 4 areas you must prepare for
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Many people aspire to work as data scientists in leading tech companies. Additionally, data scientists are in high demand globally as businesses continue to struggle with big data and extract pertinent data points. Â.
But cracking these interviews is not childâs play. It’s crucial to have the required knowledge and proficiency with fundamental concepts in data analysis. A great way to begin your preparation is to practice the interview questions for data scientists.
We have trained over 13,500 professionals, so we are aware of what it takes to succeed in even the most difficult technical interviews. Our alums consistently land offers from FAANG+ companies. An IK alum has ever received a whopping $1 as the highest offer. 267 Million!.
You have the exceptional chance to learn from knowledgeable instructors at IK who work as hiring managers and tech leads at leading Silicon Valley tech companies like Google, Facebook, Apple, and others.
Sign up for our FREE Webinar if you want to ace your upcoming tech interview.
We’ll look at some examples of interview questions for data scientists in this article. Hereâs what we will cover in this guide:
Founder of instamentor. com, sqlpad. io, posturenet. app, segue. co. X Apple, Amazon. ️Tech career, job interview, marketing, health & wellness.
Introduction of the team, relevant experience, a detailed look at the resume, how to divide Siri users into various segments, what algorithm to use, how to determine the number of clusters, and how to assess the clusters
