{"id":27854,"date":"2025-07-24T12:28:04","date_gmt":"2025-07-24T09:28:04","guid":{"rendered":"https:\/\/onkupon.com\/?post_type=courses&#038;p=27854"},"modified":"2025-07-24T09:28:05","modified_gmt":"2025-07-24T09:28:05","slug":"deep-learning","status":"publish","type":"courses","link":"https:\/\/onkupon.com\/en\/egitim\/deep-learning\/","title":{"rendered":"Deep Learning"},"content":{"rendered":"<h3 data-start=\"148\" data-end=\"186\">Deep Learning<\/h3>\n<h3 data-start=\"148\" data-end=\"186\">1 | Purpose &amp; Industry Rationale<\/h3>\n<ul data-start=\"188\" data-end=\"879\">\n<li data-start=\"188\" data-end=\"439\">\n<p data-start=\"190\" data-end=\"439\"><strong data-start=\"190\" data-end=\"217\">Explosive Market Growth<\/strong>\u2002The global deep-learning market was valued at <strong data-start=\"264\" data-end=\"293\">USD 24.53 billion in 2024<\/strong> and is forecast to reach <strong data-start=\"319\" data-end=\"349\">USD 279.60 billion by 2032<\/strong>, implying a <strong data-start=\"362\" data-end=\"398\">35 % compound annual growth rate<\/strong>.\u00a0<\/p>\n<\/li>\n<li data-start=\"440\" data-end=\"664\">\n<p data-start=\"442\" data-end=\"664\"><strong data-start=\"442\" data-end=\"467\">Soaring Talent Demand<\/strong>\u2002Job postings that reference machine-\/ deep-learning skills have been growing <strong data-start=\"544\" data-end=\"563\">\u2248 74 % per year<\/strong>, while mid-level salaries have risen <strong data-start=\"601\" data-end=\"623\">\u2248 7 % year-on-year<\/strong>.\u00a0<\/p>\n<\/li>\n<li data-start=\"665\" data-end=\"879\">\n<p data-start=\"667\" data-end=\"879\"><strong data-start=\"667\" data-end=\"691\">Premium Compensation<\/strong>\u2002Recent U.S. surveys put the total average pay for a deep-learning engineer at <strong data-start=\"770\" data-end=\"787\">USD 190 000 +<\/strong> per annum, with senior roles exceeding USD 250 000.\u00a0<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"881\" data-end=\"1075\">Deep Learning certification quantitatively validates your ability to <strong data-start=\"941\" data-end=\"1028\">design, train, optimise, and securely deploy state-of-the-art neural-network models<\/strong>, providing a globally verifiable credential.<\/p>\n<hr data-start=\"1077\" data-end=\"1080\" \/>\n<h3 data-start=\"1082\" data-end=\"1109\">2 | Deep Learning Exam Architecture<\/h3>\n<div class=\"_tableContainer_80l1q_1\">\n<div class=\"_tableWrapper_80l1q_14 group flex w-fit flex-col-reverse\">\n<table class=\"w-fit min-w-(--thread-content-width)\" data-start=\"1111\" data-end=\"1465\">\n<thead data-start=\"1111\" data-end=\"1132\">\n<tr data-start=\"1111\" data-end=\"1132\">\n<th data-start=\"1111\" data-end=\"1121\" data-col-size=\"sm\">Feature<\/th>\n<th data-start=\"1121\" data-end=\"1132\" data-col-size=\"md\">Details<\/th>\n<\/tr>\n<\/thead>\n<tbody data-start=\"1155\" data-end=\"1465\">\n<tr data-start=\"1155\" data-end=\"1211\">\n<td data-start=\"1155\" data-end=\"1171\" data-col-size=\"sm\"><strong data-start=\"1157\" data-end=\"1170\">Questions<\/strong><\/td>\n<td data-start=\"1171\" data-end=\"1211\" data-col-size=\"md\">50 multiple-choice (single correct)<\/td>\n<\/tr>\n<tr data-start=\"1212\" data-end=\"1265\">\n<td data-start=\"1212\" data-end=\"1227\" data-col-size=\"sm\"><strong data-start=\"1214\" data-end=\"1226\">Duration<\/strong><\/td>\n<td data-start=\"1227\" data-end=\"1265\" data-col-size=\"md\">120 minutes (\u2248 1 min per question)<\/td>\n<\/tr>\n<tr data-start=\"1266\" data-end=\"1290\">\n<td data-start=\"1266\" data-end=\"1282\" data-col-size=\"sm\"><strong data-start=\"1268\" data-end=\"1281\">Pass Mark<\/strong><\/td>\n<td data-start=\"1282\" data-end=\"1290\" data-col-size=\"md\">70 %<\/td>\n<\/tr>\n<tr data-start=\"1291\" data-end=\"1353\">\n<td data-start=\"1291\" data-end=\"1306\" data-col-size=\"sm\"><strong data-start=\"1293\" data-end=\"1305\">Delivery<\/strong><\/td>\n<td data-start=\"1306\" data-end=\"1353\" data-col-size=\"md\">Online, remotely proctored, instant scoring<\/td>\n<\/tr>\n<tr data-start=\"1354\" data-end=\"1414\">\n<td data-start=\"1354\" data-end=\"1371\" data-col-size=\"sm\"><strong data-start=\"1356\" data-end=\"1370\">Credential<\/strong><\/td>\n<td data-start=\"1371\" data-end=\"1414\" data-col-size=\"md\">Web + QR-verifiable<\/td>\n<\/tr>\n<tr data-start=\"1415\" data-end=\"1465\">\n<td data-start=\"1415\" data-end=\"1429\" data-col-size=\"sm\"><strong data-start=\"1417\" data-end=\"1428\">Retakes<\/strong><\/td>\n<td data-start=\"1429\" data-end=\"1465\" data-col-size=\"md\">2 free attempts within 12 months<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div class=\"sticky end-(--thread-content-margin) h-0 self-end select-none\">\n<div class=\"absolute end-0 flex items-end\">\u00a0<\/div>\n<\/div>\n<\/div>\n<\/div>\n<hr data-start=\"1467\" data-end=\"1470\" \/>\n<h3 data-start=\"1472\" data-end=\"1509\">3 | Assessed Competency Domains<\/h3>\n<p data-start=\"1510\" data-end=\"1586\"><em data-start=\"1510\" data-end=\"1584\">(each row shows a representative stem drawn from the uploaded item bank)<\/em><\/p>\n<div class=\"_tableContainer_80l1q_1\">\n<div class=\"_tableWrapper_80l1q_14 group flex w-fit flex-col-reverse\">\n<table class=\"w-fit min-w-(--thread-content-width)\" data-start=\"1588\" data-end=\"2517\">\n<thead data-start=\"1588\" data-end=\"1613\">\n<tr data-start=\"1588\" data-end=\"1613\">\n<th data-start=\"1588\" data-end=\"1597\" data-col-size=\"sm\">Domain<\/th>\n<th data-start=\"1597\" data-end=\"1613\" data-col-size=\"lg\">Example Stem<\/th>\n<\/tr>\n<\/thead>\n<tbody data-start=\"1640\" data-end=\"2517\">\n<tr data-start=\"1640\" data-end=\"1750\">\n<td data-start=\"1640\" data-end=\"1683\" data-col-size=\"sm\"><strong data-start=\"1642\" data-end=\"1682\">Activation Functions &amp; Normalisation<\/strong><\/td>\n<td data-start=\"1683\" data-end=\"1750\" data-col-size=\"lg\">\u201cWhat is the training impact of a <em data-start=\"1719\" data-end=\"1740\">Batch Normalization<\/em> layer?\u201d<\/td>\n<\/tr>\n<tr data-start=\"1751\" data-end=\"1837\">\n<td data-start=\"1751\" data-end=\"1781\" data-col-size=\"sm\"><strong data-start=\"1753\" data-end=\"1780\">Optimisation Algorithms<\/strong><\/td>\n<td data-start=\"1781\" data-end=\"1837\" data-col-size=\"lg\">\u201cIn Adam, what does the hyper-parameter \u03b2\u2081 control?\u201d<\/td>\n<\/tr>\n<tr data-start=\"1838\" data-end=\"1939\">\n<td data-start=\"1838\" data-end=\"1867\" data-col-size=\"sm\"><strong data-start=\"1840\" data-end=\"1866\">Deep CNN Architectures<\/strong><\/td>\n<td data-start=\"1867\" data-end=\"1939\" data-col-size=\"lg\">\u201cWhat is the primary advantage of shortcut connections in <em data-start=\"1927\" data-end=\"1935\">ResNet<\/em>?\u201d<\/td>\n<\/tr>\n<tr data-start=\"1940\" data-end=\"2039\">\n<td data-start=\"1940\" data-end=\"1983\" data-col-size=\"sm\"><strong data-start=\"1942\" data-end=\"1982\">Sequential Models (RNN \/ LSTM \/ GRU)<\/strong><\/td>\n<td data-start=\"1983\" data-end=\"2039\" data-col-size=\"lg\">\u201cWhy does a GRU have fewer parameters than an LSTM?\u201d<\/td>\n<\/tr>\n<tr data-start=\"2040\" data-end=\"2143\">\n<td data-start=\"2040\" data-end=\"2078\" data-col-size=\"sm\"><strong data-start=\"2042\" data-end=\"2077\">Loss Functions &amp; Regularisation<\/strong><\/td>\n<td data-start=\"2078\" data-end=\"2143\" data-col-size=\"lg\">\u201cFor which problem type is <em data-start=\"2107\" data-end=\"2119\">Focal Loss<\/em> typically preferred?\u201d<\/td>\n<\/tr>\n<tr data-start=\"2144\" data-end=\"2296\">\n<td data-start=\"2144\" data-end=\"2182\" data-col-size=\"sm\"><strong data-start=\"2146\" data-end=\"2181\">Transfer Learning &amp; Fine-Tuning<\/strong><\/td>\n<td data-start=\"2182\" data-end=\"2296\" data-col-size=\"lg\">\u201cWhen fine-tuning an ImageNet pre-trained model on a small dataset, how many early layers are usually frozen?\u201d<\/td>\n<\/tr>\n<tr data-start=\"2297\" data-end=\"2404\">\n<td data-start=\"2297\" data-end=\"2336\" data-col-size=\"sm\"><strong data-start=\"2299\" data-end=\"2335\">Model Quantisation &amp; Edge Deploy<\/strong><\/td>\n<td data-start=\"2336\" data-end=\"2404\" data-col-size=\"lg\">\u201cWhat is the effect of 8-bit quantisation on inference latency?\u201d<\/td>\n<\/tr>\n<tr data-start=\"2405\" data-end=\"2517\">\n<td data-start=\"2405\" data-end=\"2442\" data-col-size=\"sm\"><strong data-start=\"2407\" data-end=\"2441\">Security &amp; Adversarial Defence<\/strong><\/td>\n<td data-start=\"2442\" data-end=\"2517\" data-col-size=\"lg\">\u201cWhich defence strategy is most widely applied against an FGSM attack?\u201d<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div class=\"sticky end-(--thread-content-margin) h-0 self-end select-none\">\n<div class=\"absolute end-0 flex items-end\">\u00a0<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p data-start=\"2519\" data-end=\"2657\">Items target the <em data-start=\"2536\" data-end=\"2551\">Apply\u2013Analyse<\/em> tiers of Bloom\u2019s taxonomy; pilot testing produced <strong data-start=\"2602\" data-end=\"2625\">Cronbach\u2019s \u03b1 = 0.83<\/strong>, indicating high reliability.<\/p>\n<hr data-start=\"2659\" data-end=\"2662\" \/>\n<h3 data-start=\"2664\" data-end=\"2703\">4 | Certificate Value Proposition<\/h3>\n<div class=\"_tableContainer_80l1q_1\">\n<div class=\"_tableWrapper_80l1q_14 group flex w-fit flex-col-reverse\">\n<table class=\"w-fit min-w-(--thread-content-width)\" data-start=\"2705\" data-end=\"3254\">\n<thead data-start=\"2705\" data-end=\"2730\">\n<tr data-start=\"2705\" data-end=\"2730\">\n<th data-start=\"2705\" data-end=\"2715\" data-col-size=\"sm\">Benefit<\/th>\n<th data-start=\"2715\" data-end=\"2730\" data-col-size=\"lg\">Explanation<\/th>\n<\/tr>\n<\/thead>\n<tbody data-start=\"2757\" data-end=\"3254\">\n<tr data-start=\"2757\" data-end=\"2842\">\n<td data-start=\"2757\" data-end=\"2782\" data-col-size=\"sm\"><strong data-start=\"2759\" data-end=\"2781\">Global Recognition<\/strong><\/td>\n<td data-col-size=\"lg\" data-start=\"2782\" data-end=\"2842\">Badge verifies on LinkedIn \/ GitHub with a single click.<\/td>\n<\/tr>\n<tr data-start=\"2843\" data-end=\"3019\">\n<td data-start=\"2843\" data-end=\"2879\" data-col-size=\"sm\"><strong data-start=\"2845\" data-end=\"2878\">Career Velocity &amp; Salary Lift<\/strong><\/td>\n<td data-col-size=\"lg\" data-start=\"2879\" data-end=\"3019\">Certified DL specialists are hired faster and negotiate <strong data-start=\"2937\" data-end=\"2960\">upper-band salaries<\/strong> relative to peers.\u00a0<\/td>\n<\/tr>\n<tr data-start=\"3020\" data-end=\"3113\">\n<td data-start=\"3020\" data-end=\"3050\" data-col-size=\"sm\"><strong data-start=\"3022\" data-end=\"3049\">Bid &amp; Proposal Strength<\/strong><\/td>\n<td data-col-size=\"lg\" data-start=\"3050\" data-end=\"3113\">Documented expertise earns bonus points in RFP evaluations.<\/td>\n<\/tr>\n<tr data-start=\"3114\" data-end=\"3254\">\n<td data-start=\"3114\" data-end=\"3150\" data-col-size=\"sm\"><strong data-start=\"3116\" data-end=\"3149\">Continuous Learning Ecosystem<\/strong><\/td>\n<td data-col-size=\"lg\" data-start=\"3150\" data-end=\"3254\">Pass-holders receive a 25 % OptiWisdom Data Academy discount plus monthly live code-review sessions.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<div class=\"sticky end-(--thread-content-margin) h-0 self-end select-none\">\n<div class=\"absolute end-0 flex items-end\">\u00a0<\/div>\n<\/div>\n<\/div>\n<\/div>\n<hr data-start=\"3256\" data-end=\"3259\" \/>\n<h3 data-start=\"3261\" data-end=\"3299\">5 | Scientific Design &amp; Validity<\/h3>\n<ul data-start=\"3301\" data-end=\"3572\">\n<li data-start=\"3301\" data-end=\"3370\">\n<p data-start=\"3303\" data-end=\"3370\"><strong data-start=\"3303\" data-end=\"3327\">Item Response Theory<\/strong> used to remove low-discrimination items.<\/p>\n<\/li>\n<li data-start=\"3371\" data-end=\"3452\">\n<p data-start=\"3373\" data-end=\"3452\"><strong data-start=\"3373\" data-end=\"3406\">Differential Item Functioning<\/strong> audits minimise cultural \/ linguistic bias.<\/p>\n<\/li>\n<li data-start=\"3453\" data-end=\"3572\">\n<p data-start=\"3455\" data-end=\"3572\"><strong data-start=\"3455\" data-end=\"3477\">Technical Currency<\/strong>\u2002All scenarios align with Python 3.12, PyTorch 2.3, TensorFlow 2.16, and ONNX 1.17 (Q2 2025).<\/p>\n<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Deep Learning 1 | Purpose &amp; Industry Rationale Explosive Market Growth\u2002The global deep-learning market was valued at USD 24.53 billion in 2024 and is forecast to reach USD 279.60 billion by 2032, implying a 35 % compound annual growth rate.\u00a0 Soaring Talent Demand\u2002Job postings that reference machine-\/ deep-learning skills have been growing \u2248 74 % [&hellip;]<\/p>\n","protected":false},"author":18,"featured_media":27923,"template":"","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center 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