{"id":10108,"date":"2021-02-11T13:04:20","date_gmt":"2021-02-11T07:34:20","guid":{"rendered":"http:\/\/ivyproschool.com\/blog\/?p=10108"},"modified":"2021-06-10T11:19:52","modified_gmt":"2021-06-10T05:49:52","slug":"data-science-interview-questions","status":"publish","type":"post","link":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/","title":{"rendered":"Data Science Interview Questions"},"content":{"rendered":"<h1 class=\"ace-copy-paste-skip-this-tag\"><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"><\/p>\n<p><a href=\"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/\"><br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-10114\" src=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA-300x143.png\" alt=\"Interview Questions and Answers\" width=\"898\" height=\"428\" srcset=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA-300x143.png 300w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA-1024x489.png 1024w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA-768x367.png 768w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA.png 1080w\" sizes=\"auto, (max-width: 898px) 100vw, 898px\" \/><br \/>\n<\/a><\/p>\n<p>Top Data Science Interview Questions and Answers<\/span><\/h1>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Data Science interviews can often get tricky. This is because in this era of 2021, everyone aims to become a data scientist leading to tough competition and difficult interview questions. It is an interesting subject and the criticality of business depends on the insights drawn by a data scientist. Hence, higher the criticality, more the dependability and more will be the worth of the data scientist in the organization. <\/span><span class=\"attrlink url author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"><a class=\"attrlink\" href=\"https:\/\/ivyproschool.com\/our-courses\/big-data-and-analytics\/\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" data-target-href=\"https:\/\/ivyproschool.com\/our-courses\/big-data-and-analytics\/\">Ivy Professional School<\/a><\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> is a pioneer in developing the career of aspiring data scientists and analysts since 2008.\u00a0<\/span><\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Here we have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. The interviewees can help themselves by looking at these questions to broaden their spectrum about the fundamentals required for data science. We recommend you to read it till the end as we have a bonus question which is related to one of the questions from the 15 ones.\u00a0<\/span><\/div>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">1) How to select for the<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lsquo\">\u2018k\u2019<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> in k-means?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">There is an elbow method that one can use to select k for k-means clustering. This method signifies run k-means clustering on the data set where<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-apos\">&#8216;k&#8217;<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> is the number of clusters.<\/span><\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">That is why, within the sum of squares<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(WSS),<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> it is defined as the sum of the squared distance between each member of the cluster and its centroid.\u00a0<\/span><\/div>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">2) What is the significance of p-value when it comes to hypothesis testing?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">The significance of p-values are as follows:\u00a0<\/span><\/div>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">When p-value is \u2264 0.05\u00a0<\/span>\n<ul class=\"listtype-bullet listindent2 list-bullet2\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">The above equation provides strong reason against the null hypothesis; which means one can reject the null hypothesis.<\/span><\/li>\n<\/ul>\n<\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">When p-value is &gt; 0.05\u00a0<\/span>\n<ul class=\"listtype-bullet listindent2 list-bullet2\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">The above equation provides weak reason against the null hypothesis, so you accept the null hypothesis.\u00a0<\/span><\/li>\n<\/ul>\n<\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">p-value at cutoff 0.05\u00a0<\/span>\n<ul class=\"listtype-bullet listindent2 list-bullet2\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">This value is marginal, which means that it could go either way of rejecting or accepting.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">3) How to build a random forest model?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">A random forest is build from a number of decision trees. yo have to split the data into different packages and make a decision tree in each of the different groups of data. Then, the random forest brings all those trees together.<\/span><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Below are the steps to build a random forest model:<\/span><\/div>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">One has to select<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-apos\">&#8216;k&#8217;<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> features in random from a total of<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-apos\">&#8216;m&#8217;<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> features where k &lt;&lt; m<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">From the<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-apos\">&#8216;k&#8217;<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> features, calculate the node D using the best split point<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Split the node into daughter nodes using the best split<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Repeat steps two and three until leaf nodes are finalized\u00a0<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Build forest by repeating steps one to four for<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-apos\">&#8216;n&#8217;<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> times to create<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-apos\">&#8216;n&#8217;<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> number of trees\u00a0<\/span><\/li>\n<\/ul>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">4) How can one avoid to over fit the model?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Over fitting the model means that a larger amount of data is ignored for a smaller amount of a data set. Consequently, there are three main methods to avoid over fitting:<\/span><\/div>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Keeping the model simple \u2014 take fewer variables into account, thereby removing some of the noise in the training data<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Use cross-validation techniques, such as k folds cross-validation<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Use regularization techniques, such as LASSO, that penalize certain model parameters if they&#8217;re likely to cause over fitting<\/span><\/li>\n<\/ul>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">5) Define Machine Learning?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">The ability of a system to understand by learning of its own and without being explicitly programmed, is known as machine learning. It is an application of Artificial Intelligence.<\/span><\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Learn more about <\/span><span class=\"attrlink url author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"><a class=\"attrlink\" href=\"https:\/\/www.youtube.com\/watch?v=9Ra0jNsHGhI\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" data-target-href=\"https:\/\/www.youtube.com\/watch?v=9Ra0jNsHGhI\">Machine Learning using Python with Ivy Professional School.<\/a><\/span><\/div>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">6) What is the difference between uni-variate, bi-variate, and multivariate analysis?<\/span><\/h3>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Univariate data contains only one variable which we use to describe the data.\u00a0<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Bivariate data involves two different variables which we use for determining the relationship between the two variables.<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Multivariate data involves three or more variables. It contains more than one dependent variable, but the significance is same as that of the bivariate variable.<\/span><\/li>\n<\/ul>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">7) How to calculate the Euclidean distance in Python?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Let\u2019s say A1 =<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lbracket\">[0,6]<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> and A2 =<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lbracket\">[4,3].<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> Then, the Euclidean distance calculation goes like:<\/span><\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">ED = sqrt(<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(A1[0]-A2[0])**2<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> +<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(A1[1]-A2[1])**2<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> )<\/span><\/div>\n<p>&nbsp;<\/p>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">8) What is the meaning of dimensional reduction and what are its benefits?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Dimensional reduction means conversion of a data set with vast dimensions into data with lesser dimensions<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(fields).<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> However, this should not reduce the relevance of the data and should make it more concise. It reduces computation time, and improves storage. \u00a0<\/span><\/div>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">9) Can I do Machine Learning using MS-Excel?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Yes, MS-Excel is one of the platforms where Machine Learning can be performed.\u00a0<\/span><\/div>\n<p>&nbsp;<\/p>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">10) How does one treat outliers?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">There are various ways to treat outliers:<\/span><\/div>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">One can drop outliers only if it is having a null\/garbage value. By garbage value, we mean values that have no relevance. For example, a string value in the place of a numeric value is known to be garbage and can easily be removed.\u00a0<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">You can remove Extreme values, which are outliers.\u00a0<\/span><\/li>\n<\/ul>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">If you do not want to drop outliers, you can treat them as well:<\/span><\/div>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Choose a different model. Sometimes a non linear model could fit the data that is being treated as outlier by linear models.\u00a0<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Normalizing the data. This way, the extreme data points are pulled to a similar range.<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">You can use algorithms that are less affected by outliers; an example would be of random forests.\u00a0<\/span><\/li>\n<\/ul>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">11) Between Python and R, which one would you pick for text analytics, and why?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Python is better than R in terms of text analytics:<\/span><\/div>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">It has Pandas library that offers easy to use data structures as well as tools that are high in performance when it comes to data analysis.<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">It has a faster performance when it comes to text analytics<\/span><\/li>\n<\/ul>\n<p><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">R is a best-fit for machine learning than just text analysis. Hence, <a href=\"https:\/\/www.youtube.com\/playlist?list=PL6ajVQ6jyjvAA53KTnvn1kYDjafJjogNS\">python<\/a> is better.\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">12) What is a confusion matrix and how can you calculate the accuracy using it?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">A confusion matrix is a simple table we use to describe the performance of a classification model. The true values are supposed to be known for the test data. Here, the matrix compares the actual target values with those predicted by the machine learning model.<\/span><\/div>\n<div><\/div>\n<div><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-10121\" src=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/Matrix-post-300x169.jpg\" alt=\"Confusion Matrix\" width=\"948\" height=\"534\" srcset=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/Matrix-post-300x169.jpg 300w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/Matrix-post-1024x576.jpg 1024w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/Matrix-post-768x432.jpg 768w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/Matrix-post.jpg 1280w\" sizes=\"auto, (max-width: 948px) 100vw, 948px\" \/><\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">The formulae of the accuracy is :\u00a0<\/span><\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Accuracy =<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(True<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> Positive + True Negative) \/ Total Observations<\/span><\/div>\n<p>&nbsp;<\/p>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">13) What is the difference between supervised and unsupervised machine learning?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Supervised Machine learning requires training of labelled data. However, unsupervised Machine learning doesn\u2019t require labelled data.<\/span><\/div>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">14) What are the different kernels functions in SVM?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">There are four types of kernels in SVM:<\/span><\/div>\n<ul class=\"listtype-bullet listindent1 list-bullet1\">\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Linear Kernel: It is used when the data is linearly separable, i.e. using a single line.<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Polynomial kernel: It is a kernel function commonly used with support vector machines<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(SVMs)<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> and other kernelized models. It represents the similarity of vectors<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(training<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> samples) in a feature space over polynomials of the original variables. Thus providing access to non-linear models.<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Radial basis kernel: Radial Basis Kernel is a kernel function that is used in machine learning to find a non-linear classifier or regression line.<\/span><\/li>\n<li><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Sigmoid kernel: It comes from the Neural Network field, where the bipolar sigmoid function is often used as an activation function for artificial neurons. An SVM model using a sigmoid kernel function is equivalent to a two-layer, perceptron neural network.\u00a0<\/span><\/li>\n<\/ul>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">15) What is the meaning of variance?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Variance is the spread between numbers in a data set. It causes error when the model learns noise and performs bad on the data set. This can lead to high sensitivity and over fitting of the model. It is the average of the squared differences from the mean.<\/span><\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">It\u2019s time for one of our bonus interview questions now. This question is not related to the technical knowledge about data science rather answers the basic requirement a recruiter looks for in a candidate. It is important for a data scientist\/data analyst\/decision scientist to understand the exact requirement before analyzing the data. Further, it improves their understanding level and helps them deliver in time.\u00a0<\/span><\/div>\n<div><\/div>\n<h3><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Bonus Question &#8211; What is the importance of Analysis of Data?<\/span><\/h3>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Data is everywhere whether in unstructured or structured form. Yet stand-alone data makes no sense unless measured, managed or optimized. To gain valuable insights into a given set of data, the data has to lend itself to analysis using a clearly defined methodology, strategy and business goals. Data Science, which includes Analytics<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(quantitative<\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> analysis of data), Big Data management \/ reporting and Data Structure Algorithms, is the scientific process of transforming data into insight for making better decisions. One can <\/span><span class=\"attrlink url author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"><a class=\"attrlink\" href=\"https:\/\/www.youtube.com\/watch?v=SGx31GLnR5g\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" data-target-href=\"https:\/\/youtu.be\/W26eFS_eTsQ\">learn more about data science, machine learning and artificial intelligence<\/a><\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> here.\u00a0<\/span><\/div>\n<div><\/div>\n<div>Did you find the interview questions helpful? Get more tips <a href=\"https:\/\/www.youtube.com\/watch?v=lBV2Gi5ptQg&amp;t=10s\">here<\/a>.<\/div>\n<h2><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">Data Science is the future<\/span><\/h2>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">At Ivy, we have always aimed at preparing our students for the fast paced world. In this world of data analytics, we want people to learn and excel more. <\/span><span class=\"attrlink url author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"><a class=\"attrlink\" href=\"https:\/\/ivyproschool.com\/blog\/2020\/12\/30\/data-science-is-not-changing-the-world-it-is-defining-the-world\/\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" data-target-href=\"https:\/\/ivyproschool.com\/blog\/2020\/12\/30\/data-science-is-not-changing-the-world-it-is-defining-the-world\/\">Data Science is not changing the world, it is defining the world.<\/a><\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> Answering such questions will boost the confidence of the recruiter on the candidate. It will also make the recruiter abrest of the candidate&#8217;s understanding and job fitness. Responsibility is what is takes for a data scientist to play the role of a business analyst and take the entire business to another level.<\/span> <span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\">(<\/span><span class=\"attrlink url author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs h-lparen\"><a class=\"attrlink\" href=\"https:\/\/ivyproschool.com\/blog\/2020\/12\/24\/10-skills-every-business-analytics-professional-needs\/\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" data-target-href=\"https:\/\/ivyproschool.com\/blog\/2020\/12\/24\/10-skills-every-business-analytics-professional-needs\/\">Learn<\/a><\/span><span class=\"attrlink url author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"><a class=\"attrlink\" href=\"https:\/\/ivyproschool.com\/blog\/2020\/12\/24\/10-skills-every-business-analytics-professional-needs\/\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" data-target-href=\"https:\/\/ivyproschool.com\/blog\/2020\/12\/24\/10-skills-every-business-analytics-professional-needs\/\"> what it takes to become a business analyst<\/a><\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">).\u00a0<\/span><\/div>\n<div><\/div>\n<div><a href=\"https:\/\/www.youtube.com\/watch?v=Jz95uyaCmjI\">Hear it from the Expert.<\/a>Learn more about interview questions for a Full Stack Data Scientist.<\/div>\n<div><\/div>\n<div><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\">As long as the data scientist\u2019s vision does not align with that of the company\u2019s vision, the education leading to the job will be pointless. Hence, an interested candidate wanting to excel his career in the field of data science should take the best guidance. <\/span><span class=\"attrlink url author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"><a class=\"attrlink\" href=\"https:\/\/ivyproschool.com\/contact-us\/\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" data-target-href=\"https:\/\/ivyproschool.com\/contact-us\/\">Contact us<\/a><\/span><span class=\" author-d-1gg9uz65z1iz85zgdz68zmqkz84zo2qoxvz85zpz122ztq66rz79zz77zz67zmbz71zz74zyyz79zz79zqez89zy2z77ziz68zmz85zs\"> and we will help you choose the best career in the field of data science. Join our <a href=\"https:\/\/ivyproschool.com\/\">certificate<\/a> programs.<\/span><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Top Data Science Interview Questions and Answers Data Science interviews can often get tricky. This is because in this era of 2021, everyone aims to become a data scientist leading to tough competition and difficult interview questions. It is an interesting subject and the criticality of business depends on the insights drawn by a data scientist. Hence, higher the criticality, more the dependability and more will be the worth of the data scientist in the organization. Ivy Professional School is a pioneer in developing the career of aspiring data scientists and analysts since 2008.\u00a0 Here we have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. The interviewees can help themselves by looking at these questions to broaden their spectrum about the fundamentals required for data science. We recommend you to read it till the end as we have a bonus question which is related to one of the questions from the 15 ones.\u00a0 1) How to select for the \u2018k\u2019 in k-means? There is an elbow method that one can use to select k for k-means clustering. This method signifies run k-means clustering on the data set where &#8216;k&#8217; is the number of [&hellip;]<\/p>\n","protected":false},"author":1001944,"featured_media":10114,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[881,550,715],"tags":[16,877,467,115,163,511,110],"class_list":["post-10108","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science","category-interview","category-machine-learning-ai","tag-analytics-career","tag-big-data-career","tag-data-science","tag-data-scientist","tag-interview","tag-ivy-professional-school","tag-ivyproschool"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Top 15 Data Science Interview Questions | Official Blog | Ivy Pro School<\/title>\n<meta name=\"description\" content=\"We have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. Learn and Grow with Ivy Pro School.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Top 15 Data Science Interview Questions | Official Blog | Ivy Pro School\" \/>\n<meta property=\"og:description\" content=\"We have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. Learn and Grow with Ivy Pro School.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/\" \/>\n<meta property=\"og:site_name\" content=\"R vs Python: Which Analytics Tool Should You Choose for Data Science?\" \/>\n<meta property=\"article:published_time\" content=\"2021-02-11T07:34:20+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2021-06-10T05:49:52+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1080\" \/>\n\t<meta property=\"og:image:height\" content=\"516\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Anubinda\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Anubinda\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/\"},\"author\":{\"name\":\"Anubinda\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/#\\\/schema\\\/person\\\/2bc5b4bcba5e1696d75ce6924ed8ff13\"},\"headline\":\"Data Science Interview Questions\",\"datePublished\":\"2021-02-11T07:34:20+00:00\",\"dateModified\":\"2021-06-10T05:49:52+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/\"},\"wordCount\":1604,\"commentCount\":0,\"image\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/wp-content\\\/uploads\\\/2015\\\/08\\\/10th-Feb_Blog-DS-QA.png\",\"keywords\":[\"Analytics Career\",\"big data career\",\"data science\",\"data scientist\",\"interview\",\"IVY Professional School\",\"ivyproschool\"],\"articleSection\":[\"Data Science\",\"Interviews\",\"Machine Learning &amp; AI\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/\",\"url\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/\",\"name\":\"Top 15 Data Science Interview Questions | Official Blog | Ivy Pro School\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/wp-content\\\/uploads\\\/2015\\\/08\\\/10th-Feb_Blog-DS-QA.png\",\"datePublished\":\"2021-02-11T07:34:20+00:00\",\"dateModified\":\"2021-06-10T05:49:52+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/#\\\/schema\\\/person\\\/2bc5b4bcba5e1696d75ce6924ed8ff13\"},\"description\":\"We have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. Learn and Grow with Ivy Pro School.\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#primaryimage\",\"url\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/wp-content\\\/uploads\\\/2015\\\/08\\\/10th-Feb_Blog-DS-QA.png\",\"contentUrl\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/wp-content\\\/uploads\\\/2015\\\/08\\\/10th-Feb_Blog-DS-QA.png\",\"width\":1080,\"height\":516,\"caption\":\"data science interview questions and answers\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/data-science-interview-questions\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Data Science Interview Questions\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/#website\",\"url\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/\",\"name\":\"Ivy Professional School | Official Blog\",\"description\":\"Confused between R and Python for your data science journey? Discover the key differences in data visualization, handling capabilities, speed, and ease of learning.\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/#\\\/schema\\\/person\\\/2bc5b4bcba5e1696d75ce6924ed8ff13\",\"name\":\"Anubinda\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/2feb5b53215dd696c5aa800e5d4491f5402ef5f8647b9a2a6b9fe300a5885e9d?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/2feb5b53215dd696c5aa800e5d4491f5402ef5f8647b9a2a6b9fe300a5885e9d?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/2feb5b53215dd696c5aa800e5d4491f5402ef5f8647b9a2a6b9fe300a5885e9d?s=96&d=mm&r=g\",\"caption\":\"Anubinda\"},\"url\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/author\\\/anubinda\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Top 15 Data Science Interview Questions | Official Blog | Ivy Pro School","description":"We have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. Learn and Grow with Ivy Pro School.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/","og_locale":"en_US","og_type":"article","og_title":"Top 15 Data Science Interview Questions | Official Blog | Ivy Pro School","og_description":"We have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. Learn and Grow with Ivy Pro School.","og_url":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/","og_site_name":"R vs Python: Which Analytics Tool Should You Choose for Data Science?","article_published_time":"2021-02-11T07:34:20+00:00","article_modified_time":"2021-06-10T05:49:52+00:00","og_image":[{"width":1080,"height":516,"url":"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA.png","type":"image\/png"}],"author":"Anubinda","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Anubinda","Est. reading time":"8 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#article","isPartOf":{"@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/"},"author":{"name":"Anubinda","@id":"https:\/\/ivyproschool.com\/blog\/#\/schema\/person\/2bc5b4bcba5e1696d75ce6924ed8ff13"},"headline":"Data Science Interview Questions","datePublished":"2021-02-11T07:34:20+00:00","dateModified":"2021-06-10T05:49:52+00:00","mainEntityOfPage":{"@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/"},"wordCount":1604,"commentCount":0,"image":{"@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#primaryimage"},"thumbnailUrl":"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA.png","keywords":["Analytics Career","big data career","data science","data scientist","interview","IVY Professional School","ivyproschool"],"articleSection":["Data Science","Interviews","Machine Learning &amp; AI"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/","url":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/","name":"Top 15 Data Science Interview Questions | Official Blog | Ivy Pro School","isPartOf":{"@id":"https:\/\/ivyproschool.com\/blog\/#website"},"primaryImageOfPage":{"@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#primaryimage"},"image":{"@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#primaryimage"},"thumbnailUrl":"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA.png","datePublished":"2021-02-11T07:34:20+00:00","dateModified":"2021-06-10T05:49:52+00:00","author":{"@id":"https:\/\/ivyproschool.com\/blog\/#\/schema\/person\/2bc5b4bcba5e1696d75ce6924ed8ff13"},"description":"We have listed 15 fundamental interview questions that recruiters use to analyze the potential of a candidate. Learn and Grow with Ivy Pro School.","breadcrumb":{"@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#primaryimage","url":"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA.png","contentUrl":"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2015\/08\/10th-Feb_Blog-DS-QA.png","width":1080,"height":516,"caption":"data science interview questions and answers"},{"@type":"BreadcrumbList","@id":"https:\/\/ivyproschool.com\/blog\/data-science-interview-questions\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/ivyproschool.com\/blog\/"},{"@type":"ListItem","position":2,"name":"Data Science Interview Questions"}]},{"@type":"WebSite","@id":"https:\/\/ivyproschool.com\/blog\/#website","url":"https:\/\/ivyproschool.com\/blog\/","name":"Ivy Professional School | Official Blog","description":"Confused between R and Python for your data science journey? Discover the key differences in data visualization, handling capabilities, speed, and ease of learning.","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/ivyproschool.com\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/ivyproschool.com\/blog\/#\/schema\/person\/2bc5b4bcba5e1696d75ce6924ed8ff13","name":"Anubinda","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/2feb5b53215dd696c5aa800e5d4491f5402ef5f8647b9a2a6b9fe300a5885e9d?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/2feb5b53215dd696c5aa800e5d4491f5402ef5f8647b9a2a6b9fe300a5885e9d?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/2feb5b53215dd696c5aa800e5d4491f5402ef5f8647b9a2a6b9fe300a5885e9d?s=96&d=mm&r=g","caption":"Anubinda"},"url":"https:\/\/ivyproschool.com\/blog\/author\/anubinda\/"}]}},"_links":{"self":[{"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/posts\/10108","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/users\/1001944"}],"replies":[{"embeddable":true,"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/comments?post=10108"}],"version-history":[{"count":9,"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/posts\/10108\/revisions"}],"predecessor-version":[{"id":10529,"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/posts\/10108\/revisions\/10529"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/media\/10114"}],"wp:attachment":[{"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/media?parent=10108"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/categories?post=10108"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ivyproschool.com\/blog\/wp-json\/wp\/v2\/tags?post=10108"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}