{"id":2465,"date":"2026-08-10T08:56:33","date_gmt":"2026-08-10T08:56:33","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-data-pre-processing-for-data-analytics-and-data-science-2024-2\/"},"modified":"2026-08-10T08:56:33","modified_gmt":"2026-08-10T08:56:33","slug":"udemy-data-pre-processing-for-data-analytics-and-data-science-2024-2","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-data-pre-processing-for-data-analytics-and-data-science-2024-2\/","title":{"rendered":"Udemy \u2013 Data Pre-Processing for Data Analytics and Data Science 2024-2"},"content":{"rendered":"<div class=\"w-post-elm post_content\">\n<h2><span style=\"vertical-align: inherit\">Description<\/span><\/h2>\n<p><span style=\"vertical-align: inherit\">Data Pre-Processing for Data Analytics and Data Science course. The Data Preprocessing for Data Analysis and Data Science course provides students with a comprehensive understanding of the critical steps in preparing raw data for analysis. Data preprocessing is an essential step in the data science workflow, as it involves transforming, cleaning, and integrating data to ensure quality and usability for subsequent analysis. During this course, students learn various techniques and strategies for managing real-world data, which is often chaotic, inconsistent, and incomplete. They will gain hands-on experience with popular tools and libraries used for data preprocessing, such as Python and its data manipulation libraries (e.g. pandas), and explore practical examples to reinforce their learning. The key topics covered in this course are: Introduction to data preprocessing:<\/span><\/p>\n<div data-purpose=\"safely-set-inner-html:description:description\">\n<ul>\n<li><span style=\"vertical-align: inherit\">\u2013 Understanding the importance of data preprocessing in data analysis and data science<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 An overview of the data preprocessing pipeline<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Data cleaning techniques:<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Identification and management of missing values:<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Dealing with outliers and noisy data<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Fixing inconsistencies and errors in data<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Data conversion:<\/span><\/li>\n<\/ul>\n<p><span style=\"vertical-align: inherit\">Feature scaling and normalization:<\/span><\/p>\n<ul>\n<li><span style=\"vertical-align: inherit\">\u2013 Management of classified variables through coding techniques<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Dimensionality reduction methods (eg, principal component analysis)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Integration and aggregation of data:<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Merging and joining datasets:<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Manage data from multiple sources<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Collect data for analysis and visualization<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Management of text and time series data:<\/span><\/li>\n<\/ul>\n<p><span style=\"vertical-align: inherit\">Text preprocessing techniques (eg, tokenization, stemming, keyword removal):<\/span><\/p>\n<ul>\n<li><span style=\"vertical-align: inherit\">\u2013 Time series data cleaning and feature extraction<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Evaluation of data quality:<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Data profiling and exploratory data analysis<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 Data quality criteria and evaluation techniques<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">\u2013 The best methods and tools:<\/span><\/li>\n<\/ul>\n<p><span style=\"vertical-align: inherit\">Effective data cleaning and preprocessing strategies:<\/span><\/p>\n<ul>\n<li><span style=\"vertical-align: inherit\">\u2013 An introduction to popular data preprocessing libraries and tools (e.g. Pandas, NumPy)<\/span><\/li>\n<\/ul>\n<\/div>\n<h3><span style=\"vertical-align: inherit\">What you will learn in the Data Pre-Processing for Data Analytics and Data Science course<\/span><\/h3>\n<div class=\"what-you-will-learn--content-spacing--6eP1j\">\n<ul class=\"ud-unstyled-list ud-block-list what-you-will-learn--objectives-list--qsvE2 what-you-will-learn--objectives-list-two-column-layout--ED4as\">\n<li>\n<div class=\"ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm\" data-purpose=\"objective\">\n<div class=\"ud-block-list-item-content\"><span class=\"what-you-will-learn--objective-item--VZFww\"><span style=\"vertical-align: inherit\">Students will gain in-depth knowledge of exploratory data analysis and data preprocessing<\/span><\/span><\/div>\n<\/div>\n<\/li>\n<li>\n<div class=\"ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm\" data-purpose=\"objective\">\n<div class=\"ud-block-list-item-content\"><span class=\"what-you-will-learn--objective-item--VZFww\"><span style=\"vertical-align: inherit\">We learn about data cleansing and how to manage data.<\/span><\/span><\/div>\n<\/div>\n<\/li>\n<li>\n<div class=\"ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm\" data-purpose=\"objective\">\n<div class=\"ud-block-list-item-content\"><span class=\"what-you-will-learn--objective-item--VZFww\"><span style=\"vertical-align: inherit\">We will learn about how to handle duplicate and missing data.<\/span><\/span><\/div>\n<\/div>\n<\/li>\n<li>\n<div class=\"ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm\" data-purpose=\"objective\">\n<div class=\"ud-block-list-item-content\"><span class=\"what-you-will-learn--objective-item--VZFww\"><span style=\"vertical-align: inherit\">Finally, we will learn the types of outlier analysis treatment.<\/span><\/span><\/div>\n<\/div>\n<\/li>\n<li>\n<div class=\"ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm\" data-purpose=\"objective\">\n<div class=\"ud-block-list-item-content\"><span class=\"what-you-will-learn--objective-item--VZFww\"><span style=\"vertical-align: inherit\">We will learn about scaling and feature transformation techniques<\/span><\/span><\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<h3><span style=\"vertical-align: inherit\">This course is suitable for people who<\/span><\/h3>\n<ul class=\"styles--audience__list----YbP\">\n<li><span style=\"vertical-align: inherit\">This course is designed for individuals who wish to advance their careers in data analytics and data science.<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">It is also intended for professionals who want to improve their understanding of CRISP-ML(Q).<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Students from any background are invited to enroll in this program.<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Students with engineering backgrounds are encouraged to use this program to supplement their education.<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Anyone who wants to get into the data realm and analyze data.<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Data Pre-Processing for Data Analytics and Data Science course specifications<\/span><\/h3>\n<ul>\n<li><span style=\"vertical-align: inherit\">Publisher:&nbsp; <\/span><a href=\"https:\/\/href.li\/?https:\/\/www.udemy.com\/course\/data-pre-processing-for-data-analytics-and-data-science\/?couponCode=LETSLEARNNOWPP\" target=\"_blank\"><span style=\"vertical-align: inherit\">Udemy<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Instructor: <\/span><a href=\"https:\/\/downloadlynet.ir\/tag\/robert-vidal\/\"><span style=\"vertical-align: inherit\">AISPRY TUTOR<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Training level: beginner to advanced<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Training duration: 8 hours and 51 minutes<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Number of courses: 48<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Course headings<\/span><\/h3>\n<h2>&nbsp;<img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-891557 size-full\" src=\"https:\/\/downloadly.ir\/wp-content\/uploads\/2024\/03\/Data-Pre-Processing-for-Data-Analytics-and-Data-Science-1.jpg\" alt=\"Data Pre-Processing for Data Analytics and Data Science\" width=\"803\" height=\"664\"><\/h2>\n<h3><span style=\"vertical-align: inherit\">Prerequisites of the Data Pre-Processing for Data Analytics and Data Science course<\/span><\/h3>\n<ul>\n<li dir=\"ltr\" style=\"text-align: left\">Recognize the role of Python programming in EDA.<\/li>\n<li dir=\"ltr\" style=\"text-align: left\">Understand the remaining procedures in the CRISP-ML(Q) data preparation section.<\/li>\n<li dir=\"ltr\" style=\"text-align: left\">It is recommended that learners have a prior grasp of the CRISP-ML(Q) Methodology.<\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Images of Data Pre-Processing for Data Analytics and Data Science course<\/span><\/h3>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-891556 size-full\" src=\"https:\/\/downloadly.ir\/wp-content\/uploads\/2024\/03\/Data-Pre-Processing-for-Data-Analytics-and-Data-Science.jpg\" alt=\"Data Pre-Processing for Data Analytics and Data Science\" width=\"773\" height=\"284\"><\/h2>\n<h3><span style=\"vertical-align: inherit\">Sample video of the course<\/span><\/h3>\n<div style=\"width: 640px;\" class=\"wp-video\"><span class=\"mejs-offscreen\">Video Player<\/span><\/p>\n<div id=\"mep_0\" class=\"mejs-container mejs-container-keyboard-inactive wp-video-shortcode mejs-video\" tabindex=\"0\" role=\"application\" aria-label=\"Video Player\" style=\"width: 640px; height: 360px; min-width: 217px;\">\n<div class=\"mejs-inner\">\n<div class=\"mejs-mediaelement\"><mediaelementwrapper id=\"video-121032-1\"><video class=\"wp-video-shortcode\" id=\"video-121032-1_html5\" width=\"640\" height=\"360\" preload=\"metadata\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Data_Pre-Processing_for_Data_Analytics_and_Data_Science_Downloadly.ir.mp4?_=1\" style=\"width: 640px; height: 360px;\"><source type=\"video\/mp4\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Data_Pre-Processing_for_Data_Analytics_and_Data_Science_Downloadly.ir.mp4?_=1\"><a href=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Data_Pre-Processing_for_Data_Analytics_and_Data_Science_Downloadly.ir.mp4?nocache=1786095495444\">https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Data_Pre-Processing_for_Data_Analytics_and_Data_Science_Downloadly.ir.mp4<\/a><\/video><\/mediaelementwrapper><\/div>\n<div class=\"mejs-layers\">\n<div class=\"mejs-poster mejs-layer\" style=\"display: none; width: 100%; height: 100%;\"><\/div>\n<div class=\"mejs-overlay mejs-layer\" style=\"display: none; width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-loading\"><span class=\"mejs-overlay-loading-bg-img\"><\/span><\/div>\n<\/div>\n<div class=\"mejs-overlay mejs-layer\" style=\"display: none; width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-error\"><\/div>\n<\/div>\n<div class=\"mejs-overlay mejs-layer mejs-overlay-play\" style=\"width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-button\" role=\"button\" tabindex=\"0\" aria-label=\"Play\" aria-pressed=\"false\"><\/div>\n<\/div>\n<\/div>\n<div class=\"mejs-controls\">\n<div class=\"mejs-button mejs-playpause-button mejs-play\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Play\" aria-label=\"Play\" tabindex=\"0\"><\/button><\/div>\n<div class=\"mejs-time mejs-currenttime-container\" role=\"timer\" aria-live=\"off\"><span class=\"mejs-currenttime\">00:00<\/span><\/div>\n<div class=\"mejs-time-rail\"><span class=\"mejs-time-total mejs-time-slider\" role=\"slider\" tabindex=\"0\" aria-label=\"Time Slider\" aria-valuemin=\"0\" aria-valuemax=\"0\" aria-valuenow=\"0\" aria-valuetext=\"00:00\"><span class=\"mejs-time-buffering\" style=\"display: none;\"><\/span><span class=\"mejs-time-loaded\"><\/span><span class=\"mejs-time-current\"><\/span><span class=\"mejs-time-hovered no-hover\"><\/span><span class=\"mejs-time-handle\"><span class=\"mejs-time-handle-content\"><\/span><\/span><span class=\"mejs-time-float\"><span class=\"mejs-time-float-current\">00:00<\/span><span class=\"mejs-time-float-corner\"><\/span><\/span><\/span><\/div>\n<div class=\"mejs-time mejs-duration-container\"><span class=\"mejs-duration\">00:00<\/span><\/div>\n<div class=\"mejs-button mejs-volume-button mejs-mute\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Mute\" aria-label=\"Mute\" tabindex=\"0\"><\/button><a href=\"javascript:void(0);\" class=\"mejs-volume-slider\" aria-label=\"Volume Slider\" aria-valuemin=\"0\" aria-valuemax=\"100\" role=\"slider\" aria-orientation=\"vertical\"><span class=\"mejs-offscreen\">Use Up\/Down Arrow keys to increase or decrease volume.<\/span><\/p>\n<div class=\"mejs-volume-total\">\n<div class=\"mejs-volume-current\" style=\"bottom: 0px; height: 100%;\"><\/div>\n<div class=\"mejs-volume-handle\" style=\"bottom: 100%; margin-bottom: -3px;\"><\/div>\n<\/div>\n<p><\/a><\/div>\n<div class=\"mejs-button mejs-fullscreen-button\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Fullscreen\" aria-label=\"Fullscreen\" tabindex=\"0\"><\/button><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div>\n<h3><span style=\"vertical-align: inherit\">Installation guide<\/span><\/h3>\n<p><span style=\"vertical-align: inherit\">After Extract, view with your favorite Player.<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">English subtitle<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">Quality: 720p<\/span><\/p>\n<\/div>\n<h3><span style=\"vertical-align: inherit\">download link<\/span><\/h3>\n<p><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Udemy_Data_Pre-Processing_for_Data_Analytics_and_Data_Science_2024-2.part1_Downloadly.ir.rar?nocache=1786095494\"><span style=\"vertical-align: inherit\">Download part 1 \u2013 1 GB<\/span><\/a><\/p>\n<p><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Udemy_Data_Pre-Processing_for_Data_Analytics_and_Data_Science_2024-2.part2_Downloadly.ir.rar?nocache=1786095494\"><span style=\"vertical-align: inherit\">Download part 2 \u2013 1 GB<\/span><\/a><\/p>\n<p><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Udemy_Data_Pre-Processing_for_Data_Analytics_and_Data_Science_2024-2.part3_Downloadly.ir.rar?nocache=1786095494\"><span style=\"vertical-align: inherit\">Download part 3 \u2013 1 GB<\/span><\/a><\/p>\n<p><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Udemy_Data_Pre-Processing_for_Data_Analytics_and_Data_Science_2024-2.part4_Downloadly.ir.rar?nocache=1786095494\"><span style=\"vertical-align: inherit\">Download part 4 \u2013 1 GB<\/span><\/a><\/p>\n<p><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Udemy_Data_Pre-Processing_for_Data_Analytics_and_Data_Science_2024-2.part5_Downloadly.ir.rar?nocache=1786095494\"><span style=\"vertical-align: inherit\">Download part 5 \u2013 1 GB<\/span><\/a><\/p>\n<p><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Udemy_Data_Pre-Processing_for_Data_Analytics_and_Data_Science_2024-2.part6_Downloadly.ir.rar?nocache=1786095494\"><span style=\"vertical-align: inherit\">Download part 6 \u2013 112 MB<\/span><\/a><\/p>\n<p><span style=\"vertical-align: inherit\">File(s) password: www.downloadly.ir<\/span><\/p>\n<h3><span style=\"vertical-align: inherit\">Size<\/span><\/h3>\n<p><span style=\"vertical-align: inherit\">5.1 GB<\/span><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Description Data Pre-Processing for Data Analytics and Data Science course. 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