{"id":2708,"date":"2026-08-10T08:58:26","date_gmt":"2026-08-10T08:58:26","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-applied-time-series-analysis-in-python-2020-1\/"},"modified":"2026-08-10T08:58:26","modified_gmt":"2026-08-10T08:58:26","slug":"udemy-applied-time-series-analysis-in-python-2020-1","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-applied-time-series-analysis-in-python-2020-1\/","title":{"rendered":"Udemy \u2013 Applied Time Series Analysis in Python 2020-1"},"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\">Applied Time Series Analysis in Python course. This is the only course that combines the latest statistical techniques and deep learning for time series analysis. First, this course covers basic time series concepts:<\/span><\/p>\n<div data-purpose=\"safely-set-inner-html:description:description\">\n<ul>\n<li><span style=\"vertical-align: inherit\">Stationarity and Augmented Dicker-Fuller Test<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">being seasonal<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">white noise<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Random walk<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Autoregression<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Moving Average<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">ACF and PACF,<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Model selection with AIC (Akaike information criterion)<\/span><\/li>\n<\/ul>\n<p><span style=\"vertical-align: inherit\">Then, we apply more sophisticated statistical models to time series forecasting:<\/span><\/p>\n<ul>\n<li><span style=\"vertical-align: inherit\">ARIMA (autoregressive integrated moving average model)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">SARIMA (Seasonal Autoregressive Integrated Moving Average Model)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">SARIMAX (integrated moving average model of seasonal regression with exogenous variables)<\/span><\/li>\n<\/ul>\n<p><span style=\"vertical-align: inherit\">We also cover multiple time series forecasting with:<\/span><\/p>\n<ul>\n<li><span style=\"vertical-align: inherit\">VAR (vector autoregression)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">VARMA (vector autoregressive moving average model)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">VARMAX (vector autoregressive moving average model with exogenous variable)<\/span><\/li>\n<\/ul>\n<p><span style=\"vertical-align: inherit\">Next, we move on to the deep learning section, where we use Tensorflow to apply various deep learning techniques to time series analysis:<\/span><\/p>\n<ul>\n<li><span style=\"vertical-align: inherit\">Simple linear model (1-layer neural network)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">DNN (Deep Neural Network)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">CNN (Convolutional Neural Network)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">LSTM (long short term memory)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">CNN + LSTM models<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">ResNet (residual networks)<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">LSTM autoregression<\/span><\/li>\n<\/ul>\n<\/div>\n<h3><span style=\"vertical-align: inherit\">What you will learn in the Applied Time Series Analysis in Python course<\/span><\/h3>\n<div class=\"what-you-will-learn--content-spacing--6eP1j show-more-module--container--teP7C\">\n<div class=\"show-more-module--content--Rw-xr show-more-module--with-gradient--f4HoJ\">\n<div>\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\">Descriptive statistics versus inferential statistics<\/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\">Random walk model<\/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\">Moving average model<\/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\">Autoregression<\/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\">ACF and PACF<\/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\">stable<\/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\">Arima, Sarima, Sarimax<\/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\">Hot, hot, hot<\/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\">Use deep learning to analyze time series with TensorFlow<\/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\">Linear models, DNN, LSTM, CNN, ResNet<\/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\">Automate time series analysis with Prophet<\/span><\/span><\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\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\">Beginning data scientists looking to gain experience with time series<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Deep learning beginners curious about time series<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Professional data scientists who need time series analysis<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Data scientists looking to migrate from R to Python<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Specifications of Applied Time Series Analysis in Python course<\/span><\/h3>\n<ul>\n<li><span style=\"vertical-align: inherit\">Publisher:&nbsp; <\/span><a href=\"https:\/\/href.li\/?https:\/\/www.udemy.com\/course\/applied-time-series-analysis-in-python\/?couponCode=ST13MT40224\" target=\"_blank\"><span style=\"vertical-align: inherit\">Udemy<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Teacher: <\/span><a href=\"https:\/\/downloadlynet.ir\/tag\/marco-peixeiro\/\"><span style=\"vertical-align: inherit\">Marco Peixeiro<\/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: 6 hours and 5 minutes<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Number of courses: 40<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Course topics on 7\/2022<\/span><\/h3>\n<h2>&nbsp;<img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-894556 size-full\" src=\"https:\/\/downloadly.ir\/wp-content\/uploads\/2024\/04\/Applied-Time-Series-Analysis-in-Python-1.jpg\" alt=\"Applied Time Series Analysis in Python\" width=\"814\" height=\"523\"><\/h2>\n<h3><span style=\"vertical-align: inherit\">Prerequisites of the Applied Time Series Analysis in Python course<\/span><\/h3>\n<ul>\n<li dir=\"ltr\" style=\"text-align: left\">Basic knowledge of Python<\/li>\n<li dir=\"ltr\" style=\"text-align: left\">Basic knowledge of deep learning<\/li>\n<li dir=\"ltr\" style=\"text-align: left\">Jupyter notebook installed (or access to Google Colab)<\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Course images<\/span><\/h3>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-894555 size-full\" src=\"https:\/\/downloadly.ir\/wp-content\/uploads\/2024\/04\/Applied-Time-Series-Analysis-in-Python.jpg\" alt=\"Applied Time Series Analysis in Python\" width=\"749\" height=\"303\"><\/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-122506-1\"><video class=\"wp-video-shortcode\" id=\"video-122506-1_html5\" width=\"640\" height=\"360\" preload=\"metadata\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Applied_Time_Series_Analysis_in_Python_Downloadly.ir.mp4?_=1\" style=\"width: 640px; height: 360px;\"><source type=\"video\/mp4\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Applied_Time_Series_Analysis_in_Python_Downloadly.ir.mp4?_=1\"><a href=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Applied_Time_Series_Analysis_in_Python_Downloadly.ir.mp4?nocache=1786096079558\">https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Applied_Time_Series_Analysis_in_Python_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_Applied_Time_Series_Analysis_in_Python_2020-1.part1_Downloadly.ir.rar?nocache=1786096078\"><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_Applied_Time_Series_Analysis_in_Python_2020-1.part2_Downloadly.ir.rar?nocache=1786096078\"><span style=\"vertical-align: inherit\">Download part 2 \u2013 540 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\">1.5 GB<\/span><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Description Applied Time Series Analysis in Python course. 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