DSI ACE PREP - Data Science Interview: Prep for SQL, Panda, Python, R Language, Machine Learning, DBMS and RDBMS – And More – The Full Data Scientist Interview Handbook
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Are YOU looking for a data scientist job?
Then keep reading
The median annual salary for a Data Scientist is $98,230, according to the Bureau of Labor Statistics.
Data science job postings grew by 31% over the past few years, while data science job searches only rose by 14% over the same period. This high demand has led to a shortage of over 150,000 data science professionals.
Glassdoor ranks data science, as the #2 job in America for 2022, and this trend is likely to continue.
Data science is one of the most in-demand professions today. Its also one of the highest paid and offers great benefits. Its also one of the hardest to get into, with only 1 in every 10 applicants being accepted by top companies like Google and Facebook. And as such, there are many challenges that come with this profession such as finding your dream job, getting through interviews and landing the offer letter.
You dont have to be intimidated by interviews anymore! With this Data Science Interview book, youll be prepared for questions compiled from real data scientists who work at top companies including Google, Facebook, and Amazon & NASA.
You can use this Data Science Interview book as an effective study guide before going into any interview or even just brush up on some concepts if you feel confident about them already. Either way itll be worth it because we know how difficult it is to find good jobs in todays market! Dont let another opportunity pass you by - buy this book now and start preparing for your next big data science interview!
CONTENTS:
Background Interview Questions and Solutions
Careers in Data Science
Probability
Linear Algebra
Curse of Dimensionality
Support Vector Machine (SVM)
Overfitting and Underfitting
Random Forest in R
Clustered and Non-Clustered Indexes
Data Integrity
Interview Questions on Technical Abilities
Interview on Personal Concerns
Interview Questions on Communication and Leadership
Behavioral Interview Questions
Interview Questions Top Companies
Topics covered in this book include:
Then keep reading
The median annual salary for a Data Scientist is $98,230, according to the Bureau of Labor Statistics.
Data science job postings grew by 31% over the past few years, while data science job searches only rose by 14% over the same period. This high demand has led to a shortage of over 150,000 data science professionals.
Glassdoor ranks data science, as the #2 job in America for 2022, and this trend is likely to continue.
Data science is one of the most in-demand professions today. Its also one of the highest paid and offers great benefits. Its also one of the hardest to get into, with only 1 in every 10 applicants being accepted by top companies like Google and Facebook. And as such, there are many challenges that come with this profession such as finding your dream job, getting through interviews and landing the offer letter.
You dont have to be intimidated by interviews anymore! With this Data Science Interview book, youll be prepared for questions compiled from real data scientists who work at top companies including Google, Facebook, and Amazon & NASA.
You can use this Data Science Interview book as an effective study guide before going into any interview or even just brush up on some concepts if you feel confident about them already. Either way itll be worth it because we know how difficult it is to find good jobs in todays market! Dont let another opportunity pass you by - buy this book now and start preparing for your next big data science interview!
CONTENTS:
- INTRODUCTION
Background Interview Questions and Solutions
Careers in Data Science
- CHAPTER 1: MASTERING THE BASICS
Probability
Linear Algebra
- CHAPTER 2: PYTHON
- CHAPTER 3: PANDA
- CHAPTER 4: MACHINE LEARNING
Curse of Dimensionality
Support Vector Machine (SVM)
Overfitting and Underfitting
- CHAPTER 5: R LANGUAGE
- CSV files in R Programming
Random Forest in R
- K-MEANS Clustering
- CHAPTER 6: SQL
- DBMS and RDBMS
- RDBMS
- MYSQL
Clustered and Non-Clustered Indexes
Data Integrity
- SQL Cursor
- CHAPTER 7: DATA WRANGLING
- CHAPTER 8: DATA SCIENCE INTERVIEW EXTRA
Interview Questions on Technical Abilities
Interview on Personal Concerns
Interview Questions on Communication and Leadership
Behavioral Interview Questions
Interview Questions Top Companies
- CONCLUSION
Topics covered in this book include:
- Basic data science interview questions
- Python interview questions
- Panda questions
- Machine learning interview questions
- R Language interview questions
- SQL questions and many more
DSI ACE PREP: author's other books
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Probyto Data Science and Consulting Pvt. Ltd.
Wade Briggs
Sanders Hillary
Madhavan
Joel Grus [Grus
![Thomas Mailund [Thomas Mailund] - Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist](/uploads/posts/book/119629/thumbs/thomas-mailund-thomas-mailund-beginning-data.jpg)
Thomas Mailund [Thomas Mailund]
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DATA SCIENCE
INTERVIEW
GUIDE
ACE-PREP
ABOUT THE AUTHOR
ACE-PREP
ACE PREP are researchers
Based in London, England.
The ACE-PREP is a collective; we work with the most senior academic researchers, writers and knowledge makers.
We are in the changing lives business.
Copyright 2022 by (United Arts Publishing, England.) - All rights reserved.
This document is geared towards providing exact and reliable information in regards to the topic and issue covered. The publication is sold with the idea that the publisher is not required to render accounting, officially permitted, or otherwise, qualified services. If advice is necessary, legal or professional, a practised individual in the profession should be ordered.
- From a Declaration of Principles which was accepted and approved equally by a Committee of the American Bar Association and a Committee of Publishers and Associations.
In no way is it legal to reproduce, duplicate, or transmit any part of this document in either electronic means or in printed format. Recording of this publication is strictly prohibited and any storage of this document is not allowed unless with written permission from the publisher. All rights reserved.
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Respective authors own all copyrights not held by the publisher.
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The trademarks that are used are without any consent, and the publication of the trademark is without permission or backing by the trademark owner. All trademarks and brands within this book are for clarifying purposes only and are the owned by the owners themselves, not affiliated with this document.
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First published by Mastership Books (London, UK), 2022
I S B N: 978-1-915002-10-5
Text Copyright United Arts Publishing
All rights reserved. Without limiting the rights under copyright reserved above, no part of this publication may be reproduced, stored in or introduced into a retrival system, or transmitted, in any form or by any means (electronic, mechanical, photocopying, recording or otherwise), without the prior written permission of both the copyright owner and the above publisher of this book.
Cover design by Rich United Arts Publishing (UK)
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ISBN: 978-1-915002-10-5 - (paperback)
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Title: Data Science Interview Guide
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DATA
SCIENCE
INTERVIEW
GUIDE
An investment in knowledge pays the best interest
- Benjamin Franklin.
CONTENTS
CHAPTER
CHAPTER:
CHAPTER
CHAPTER
CHAPTER
CHAPTER
CHAPTER
CHAPTER
INTRODUCTION
Meaning of Data Science
D ata science is an interdisciplinary subject that mines raw data, analyzes it, and creates patterns from which valuable insights may be extracted. Data science is based on a foundation of statistics, computer science, machine learning, deep learning, data analysis, data visualization, and a variety of other technologies.
Because of the importance of data, data science has grown in popularity in recent times. Data is seen as the new oil, which may be extremely useful to all parties when correctly examined and utilized. Not only that but a data scientist is exposed to work in many disciplines, tackling real-world challenges using cutting-edge technologies. The most popular real-time use is fast food delivery in applications like Uber Eats, which assists the delivery worker by showing the quickest path from the restaurant to the location. Data Science is also utilized in item recommendation algorithms on e-commerce sites such as Amazon, Flipkart, and others, which suggest items to users according to their search history. Data Science is also becoming extremely prevalent in detecting fraud involved in credit-based financial applications, not simply recommendation systems. While solving challenges that assist drive business and strategic goals, a skilled data scientist can understand data, innovate, and bring forth creativity. As a result, it has fast become one of the most highly paid and sought after employment roles of the twenty-first century.
Background Interview Questions and Solutions
1. What exactly does the term "Data Science" mean?
Data Science is an interdisciplinary discipline that encompasses a variety of scientific procedures, algorithms, tools, and machine learning algorithms that work together to uncover common patterns and gain useful insights from raw input data using statistical and mathematical analysis.
Gathering business needs and related data is the first step; data cleansing, data staging, data warehousing, and data architecture are all procedures in the data acquisition process. Exploring, mining, and analyzing data are all tasks that data processing does, and the results may then be utilized to provide a summary of the data's insights.
Following the exploratory phases, the cleansed data is exposed to many algorithms, such as predictive analysis, regression, text mining, pattern recognition, and so on, depending on the needs. In the final last stage, the outcomes are aesthetically appealingly when conveyed to the business. This is where the ability to see data, report on it, and use other business intelligence tools come into play.
2. What is the difference between data science and data analytics?
Data science is altering data using a variety of technical analysis approaches to derive useful insights that data analysts may apply to their business scenarios.
Data analytics is concerned with verifying current hypotheses and facts and answering questions for a more efficient and successful business decision-making process.
Data Science fosters innovation by providing answers to questions that help people make connections and solve challenges in the future. Data analytics is concerned with removing current meaning from past context, whereas data science is concerned with predictive modelling.
Data science is a wide topic that employs a variety of mathematical and scientific tools and methods to solve complicated issues. In contrast, data analytics is a more focused area that employs fewer statistical and visualization techniques to solve particular problems.
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