{"id":12893,"date":"2026-06-25T17:56:54","date_gmt":"2026-06-25T12:26:54","guid":{"rendered":"https:\/\/www.scaler.com\/blog\/?p=12893"},"modified":"2026-08-12T18:06:57","modified_gmt":"2026-08-12T12:36:57","slug":"ml-engineer-roadmap","status":"publish","type":"post","link":"https:\/\/www.scaler.com\/blog\/ml-engineer-roadmap\/","title":{"rendered":"ML Engineer Roadmap 2026: From Beginner to Job-Ready"},"content":{"rendered":"\n

A few years back, the ability to build an ML model was good enough to set you apart from the crowd. Now, companies expect their ML engineers to perform many tasks with big data, including training models, putting them into production, monitoring their performance, and developing applications on top of LLMs and Generative AI.<\/p>\n\n\n

The challenge isn’t a lack of resources; rather, it’s knowing which resources to use and in what sequence. With this machine learning engineer roadmap, you\u2019ll go from mathematics and Python to machine learning, deep learning, MLOps, and finally advanced AI.<\/p>\n\n\n

<\/span>What Does a Machine Learning Engineer Actually Do?<\/strong><\/span><\/h2>\n\n\n

The myth about Machine Learning Engineers is that most of their work revolves around training ML models. The truth is that the task of developing a model is just one part of what a Machine Learning Engineer does. A Machine Learning Engineer is responsible for taking an ML solution from experimentation to production.\u00a0<\/p>\n\n\n

If you’re curious about what does an ML engineer do, here is what\u2019s mainly expected:<\/p>\n\n\n

    \n
  • Preparing and processing data<\/li>\n\n\n
  • Building and training machine learning models<\/li>\n\n\n
  • Evaluating model performance<\/li>\n\n\n
  • Deploying models to production environments<\/li>\n\n\n
  • Monitoring model accuracy and reliability<\/li>\n\n\n
  • Automating ML workflows and pipelines<\/li>\n\n\n
  • Collaborating with software, data, and product teams<\/li>\n<\/ul>\n\n\n

    Machine Learning Engineers are often confused with Data Scientists and AI Engineers, but their responsibilities are different.<\/p>\n\n\n

    Role\u00a0<\/strong><\/td>Primary Focus\u00a0<\/strong><\/td><\/tr>
    Data Scientist\u00a0<\/td>Analyzing data, generating insights, and building predictive models\u00a0<\/td><\/tr>
    Machine Learning Engineer\u00a0<\/td>Building, deploying, scaling, and maintaining ML systems in production\u00a0<\/td><\/tr>
    AI Engineer\u00a0<\/td>Developing AI-powered applications, including LLMs, agents, and generative AI systems\u00a0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nScaler Carousel<\/title>\n\n<!-- Plus Jakarta Sans Font -->\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Plus+Jakarta+Sans:wght@400;500;600;700&display=swap\" rel=\"stylesheet\">\n<!-- Swiper CSS -->\n<link rel=\"stylesheet\" href=\"https:\/\/cdn.jsdelivr.net\/npm\/swiper@11\/swiper-bundle.min.css\">\n\n<style>\n.scaler-carousel {\n font-family: 'Plus Jakarta Sans', sans-serif;\n max-width: 900px;\n margin: 24px auto;\n padding: 0;\n box-sizing: border-box;\n}\n.scaler-carousel *,\n.scaler-carousel *::before,\n.scaler-carousel *::after {\n box-sizing: border-box;\n}\n\n\/* Header *\/\n.scaler-header {\n text-align: center;\n margin-bottom: 20px;\n}\n.scaler-header-title {\n font-size: 22px;\n font-weight: 700;\n color: #1a1a2e;\n margin: 0 0 6px;\n line-height: 1.2;\n}\n.scaler-header-subtitle {\n font-size: 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5px;\n}\n.scaler-title {\n font-size: 16px;\n font-weight: 700;\n color: #111827;\n margin: 0;\n line-height: 1.35;\n}\n.scaler-desc {\n font-size: 13px;\n color: #6b7280;\n margin: 0;\n line-height: 1.45;\n}\n\n\/* Stats row *\/\n.scaler-stats {\n display: flex;\n border-top: 1px solid #e5e7eb;\n border-bottom: 1px solid #e5e7eb;\n padding: 12px 0;\n}\n.scaler-stat {\n display: flex;\n flex-direction: column;\n align-items: center;\n gap: 2px;\n flex: 1;\n min-width: 0;\n text-align: center;\n}\n.scaler-stat:not(:last-child) {\n border-right: 1px solid #d1d5db;\n}\n.scaler-stat-value {\n font-size: 14px;\n font-weight: 700;\n color: #111827;\n white-space: nowrap;\n}\n.scaler-stat-label {\n font-size: 12px;\n color: #9ca3af;\n}\n\n\/* Company logos *\/\n.scaler-logos {\n display: flex;\n align-items: center;\n gap: 12px;\n flex-wrap: nowrap;\n}\n.scaler-company-logo {\n height: 20px !important;\n width: auto !important;\n max-width: 70px;\n object-fit: contain;\n display: inline-block;\n}\n.scaler-logo-more {\n font-size: 12px;\n color: #9ca3af;\n white-space: nowrap;\n}\n.scaler-logo-strip {\n display: block;\n width: 100% !important;\n max-width: 100%;\n min-width: 0;\n height: auto !important;\n object-fit: contain;\n}\n\n\/* CTA *\/\n.scaler-card-btns {\n margin-top: auto;\n}\n.scaler-card-btns button {\n display: flex;\n align-items: center;\n justify-content: center;\n gap: 8px;\n width: 100%;\n padding: 12px 16px;\n border: none;\n border-radius: 10px;\n background-color: #255aad;\n color: #ffffff;\n font-family: 'Plus Jakarta Sans', sans-serif;\n font-size: 14px;\n font-weight: 600;\n cursor: pointer;\n text-decoration: none;\n transition: opacity 0.15s ease;\n}\n.scaler-card-btns button:hover,\n.scaler-card-btns button:focus {\n opacity: 0.88;\n color: #ffffff;\n}\n.scaler-card-btns button svg {\n flex-shrink: 0;\n}\n\n@media (max-width: 1000px) {\n .scaler-carousel { max-width: 96vw; }\n}\n<\/style>\n\n\n<div class=\"scaler-carousel\">\n <div class=\"scaler-header\">\n <h2 class=\"scaler-header-title\"><span class=\"ez-toc-section\" id=\"transform-your-career\"><\/span>Transform Your Career<span class=\"ez-toc-section-end\"><\/span><\/h2>\n <p class=\"scaler-header-subtitle\">Choose from our industry-leading programs designed for career success<\/p>\n <\/div>\n\n <div class=\"swiper scaler-swiper\">\n <div class=\"swiper-wrapper\">\n\n <!-- CARD 1 -->\n <div class=\"swiper-slide\">\n <div class=\"scaler-card\">\n <div class=\"scaler-badge\">NSDC Certified<\/div>\n <div class=\"scaler-card-top\">\n <div class=\"scaler-icon-wrap\">\n <svg width=\"26\" height=\"26\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><polyline points=\"16 18 22 12 16 6\"\/><polyline points=\"8 6 2 12 8 18\"\/><\/svg>\n <\/div>\n <div class=\"scaler-card-top-content\">\n <h3 class=\"scaler-title\">Modern Software and AI Engineering Program<\/h3>\n <p class=\"scaler-desc\">Master full-stack development with AI integration<\/p>\n <\/div>\n <\/div>\n <div class=\"scaler-stats\">\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">12 Months<\/span><span class=\"scaler-stat-label\">Duration<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">AI-Led<\/span><span class=\"scaler-stat-label\">Curriculum<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">Career Support<\/span><span class=\"scaler-stat-label\">Support<\/span><\/div>\n <\/div>\n <div class=\"scaler-logos\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/2\/2f\/Google_2015_logo.svg\" alt=\"Google\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/a\/a9\/Amazon_logo.svg\" alt=\"Amazon\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/4\/42\/Paytm_logo.png\" alt=\"Paytm\" loading=\"lazy\">\n <span class=\"scaler-logo-more\">+1000 more<\/span>\n <\/div>\n <div class=\"scaler-card-btns\">\n <button onclick=\"window.open('https:\/\/www.scaler.com\/academy\/', '_blank')\">\n Go to Program\n <svg width=\"14\" height=\"14\" viewBox=\"0 0 16 16\" fill=\"none\" aria-hidden=\"true\"><path d=\"M3 8H13M13 8L9 4M13 8L9 12\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg>\n <\/button>\n <\/div>\n <\/div>\n <\/div>\n\n <!-- CARD 2 -->\n <div class=\"swiper-slide\">\n <div class=\"scaler-card\">\n <div class=\"scaler-badge\">NSDC Certified<\/div>\n <div class=\"scaler-card-top\">\n <div class=\"scaler-icon-wrap\">\n <svg width=\"26\" height=\"26\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><ellipse cx=\"12\" cy=\"5\" rx=\"9\" ry=\"3\"\/><path d=\"M3 5v14c0 1.66 4.03 3 9 3s9-1.34 9-3V5\"\/><path d=\"M3 12c0 1.66 4.03 3 9 3s9-1.34 9-3\"\/><\/svg>\n <\/div>\n <div class=\"scaler-card-top-content\">\n <h3 class=\"scaler-title\">Modern Data Science and ML with specialisation in AI<\/h3>\n <p class=\"scaler-desc\">Advanced data science techniques with AI specialization<\/p>\n <\/div>\n <\/div>\n <div class=\"scaler-stats\">\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">12 Months<\/span><span class=\"scaler-stat-label\">Duration<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">AI-Led<\/span><span class=\"scaler-stat-label\">Curriculum<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">Career Support<\/span><span class=\"scaler-stat-label\">Support<\/span><\/div>\n <\/div>\n <div class=\"scaler-logos\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/2\/2f\/Google_2015_logo.svg\" alt=\"Google\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/a\/a9\/Amazon_logo.svg\" alt=\"Amazon\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/4\/42\/Paytm_logo.png\" alt=\"Paytm\" loading=\"lazy\">\n <span class=\"scaler-logo-more\">+1000 more<\/span>\n <\/div>\n <div class=\"scaler-card-btns\">\n <button onclick=\"window.open('https:\/\/www.scaler.com\/data-science-course\/', '_blank')\">\n Go to Program\n <svg width=\"14\" height=\"14\" viewBox=\"0 0 16 16\" fill=\"none\" aria-hidden=\"true\"><path d=\"M3 8H13M13 8L9 4M13 8L9 12\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg>\n <\/button>\n <\/div>\n <\/div>\n <\/div>\n\n <!-- CARD 3 -->\n <div class=\"swiper-slide\">\n <div class=\"scaler-card\">\n <div class=\"scaler-badge\">NSDC Certified<\/div>\n <div class=\"scaler-card-top\">\n <div class=\"scaler-icon-wrap\">\n <svg width=\"26\" height=\"26\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M12 2L13.5 8.5L20 10L13.5 11.5L12 18L10.5 11.5L4 10L10.5 8.5L12 2Z\"\/><\/svg>\n <\/div>\n <div class=\"scaler-card-top-content\">\n <h3 class=\"scaler-title\">Advanced AIML with Specialisation in Agentic AI<\/h3>\n <p class=\"scaler-desc\">Deep dive into AIML with focus on Agentic systems<\/p>\n <\/div>\n <\/div>\n <div class=\"scaler-stats\">\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">12 Months<\/span><span class=\"scaler-stat-label\">Duration<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">AI-Led<\/span><span class=\"scaler-stat-label\">Curriculum<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">Career Support<\/span><span class=\"scaler-stat-label\">Support<\/span><\/div>\n <\/div>\n <div class=\"scaler-logos\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/2\/2f\/Google_2015_logo.svg\" alt=\"Google\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/a\/a9\/Amazon_logo.svg\" alt=\"Amazon\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/4\/42\/Paytm_logo.png\" alt=\"Paytm\" loading=\"lazy\">\n <span class=\"scaler-logo-more\">+1000 more<\/span>\n <\/div>\n <div class=\"scaler-card-btns\">\n <button onclick=\"window.open('https:\/\/www.scaler.com\/ai-machine-learning-course\/', '_blank')\">\n Go to Program\n <svg width=\"14\" height=\"14\" viewBox=\"0 0 16 16\" fill=\"none\" aria-hidden=\"true\"><path d=\"M3 8H13M13 8L9 4M13 8L9 12\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg>\n <\/button>\n <\/div>\n <\/div>\n <\/div>\n\n <!-- CARD 4 -->\n <div class=\"swiper-slide\">\n <div class=\"scaler-card\">\n <div class=\"scaler-badge\">NSDC Certified<\/div>\n <div class=\"scaler-card-top\">\n <div class=\"scaler-icon-wrap\">\n <svg width=\"26\" height=\"26\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\">\n <path d=\"M17.5 19H9a7 7 0 1 1 6.71-9h1.79a4.5 4.5 0 1 1 0 9Z\" \/>\n <path d=\"M9.2 15.2a3 3 0 1 0 4.24-4.24\" \/>\n <\/svg>\n <\/div>\n <div class=\"scaler-card-top-content\">\n <h3 class=\"scaler-title\">DevOps, Cloud & AI Platform Engineering<\/h3>\n <p class=\"scaler-desc\">Build and manage AI-powered cloud infrastructure<\/p>\n <\/div>\n <\/div>\n <div class=\"scaler-stats\">\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">12 Months<\/span><span class=\"scaler-stat-label\">Duration<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">AI-Led<\/span><span class=\"scaler-stat-label\">Curriculum<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">Career Support<\/span><span class=\"scaler-stat-label\">Support<\/span><\/div>\n <\/div>\n <div class=\"scaler-logos\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/2\/2f\/Google_2015_logo.svg\" alt=\"Google\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/a\/a9\/Amazon_logo.svg\" alt=\"Amazon\" loading=\"lazy\">\n <img decoding=\"async\" class=\"scaler-company-logo\" src=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/4\/42\/Paytm_logo.png\" alt=\"Paytm\" loading=\"lazy\">\n <span class=\"scaler-logo-more\">+1000 more<\/span>\n <\/div>\n <div class=\"scaler-card-btns\">\n <button onclick=\"window.open('https:\/\/www.scaler.com\/devops-course\/', '_blank')\">\n Go to Program\n <svg width=\"14\" height=\"14\" viewBox=\"0 0 16 16\" fill=\"none\" aria-hidden=\"true\"><path d=\"M3 8H13M13 8L9 4M13 8L9 12\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg>\n <\/button>\n <\/div>\n <\/div>\n <\/div>\n\n <!-- CARD 5 -->\n <div class=\"swiper-slide\">\n <div class=\"scaler-card\">\n <div class=\"scaler-badge\">NSDC Certified<\/div>\n <div class=\"scaler-card-top\">\n <div class=\"scaler-icon-wrap\">\n <svg width=\"26\" height=\"26\" viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\">\n <line x1=\"3\" y1=\"22\" x2=\"21\" y2=\"22\" \/>\n <line x1=\"6\" y1=\"18\" x2=\"6\" y2=\"11\" \/>\n <line x1=\"10\" y1=\"18\" x2=\"10\" y2=\"11\" \/>\n <line x1=\"14\" y1=\"18\" x2=\"14\" y2=\"11\" \/>\n <line x1=\"18\" y1=\"18\" x2=\"18\" y2=\"11\" \/>\n <polygon points=\"12 2 20 7 4 7\" \/>\n <\/svg>\n <\/div>\n <div class=\"scaler-card-top-content\">\n <h3 class=\"scaler-title\">AI Engineering Advanced Certification by IIT-Roorkee<\/h3>\n <p class=\"scaler-desc\">Premier AI engineering certification from IIT-Roorkee<\/p>\n <\/div>\n <\/div>\n <div class=\"scaler-stats\">\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">3 Months<\/span><span class=\"scaler-stat-label\">Duration<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">AI-Led<\/span><span class=\"scaler-stat-label\">Curriculum<\/span><\/div>\n <div class=\"scaler-stat\"><span class=\"scaler-stat-value\">Career Support<\/span><span class=\"scaler-stat-label\">Support<\/span><\/div>\n <\/div>\n <div class=\"scaler-logos\">\n <img decoding=\"async\" class=\"scaler-logo-strip\" src=\"https:\/\/scaler-blog-prod-wp-content.s3.ap-south-1.amazonaws.com\/wp-content\/uploads\/2026\/07\/08135139\/iitr-icons-strip.png\" alt=\"Program highlights\" loading=\"lazy\">\n <\/div>\n <div class=\"scaler-card-btns\">\n <button onclick=\"window.open('https:\/\/www.scaler.com\/iit-roorkee-advanced-ai-engineering-course\/', '_blank')\">\n Go to Program\n <svg width=\"14\" height=\"14\" viewBox=\"0 0 16 16\" fill=\"none\" aria-hidden=\"true\"><path d=\"M3 8H13M13 8L9 4M13 8L9 12\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg>\n <\/button>\n <\/div>\n <\/div>\n <\/div>\n\n <!-- Continue for remaining cards (6\u20138) using same pattern -->\n\n <\/div>\n <div class=\"swiper-button-next\"><\/div>\n <div class=\"swiper-button-prev\"><\/div>\n <div class=\"swiper-pagination\"><\/div>\n <\/div>\n<\/div>\n\n<!-- Swiper.js -->\n<script src=\"https:\/\/cdn.jsdelivr.net\/npm\/swiper@11\/swiper-bundle.min.js\"><\/script>\n<script>\ndocument.addEventListener(\"DOMContentLoaded\", function () {\n const pathParts = window.location.pathname.split(\"\/\").filter(Boolean);\n const slug = pathParts[pathParts.length - 1] || \"\";\n const readableSlug = encodeURIComponent(slug);\n const buttons = document.querySelectorAll(\".scaler-card-btns button\");\n\n buttons.forEach((btn) => {\n const baseURL = btn.getAttribute(\"onclick\").match(\/'(.*?)'\/)[1];\n if (!baseURL.includes(\"utm_source=\")) {\n const separator = baseURL.includes(\"?\") ? \"&\" : \"?\";\n const updatedURL = `${baseURL}${separator}utm_source=blog&utm_medium=program_carousel&utm_content=${readableSlug}`;\n btn.setAttribute(\"onclick\", `window.open('${updatedURL}', '_blank')`);\n }\n });\n\n new Swiper(\".scaler-swiper\", {\n slidesPerView: 1,\n spaceBetween: 28,\n grabCursor: true,\n navigation: { nextEl: \".swiper-button-next\", prevEl: \".swiper-button-prev\" },\n pagination: { el: \".swiper-pagination\", dynamicBullets: true, clickable: true },\n breakpoints: { 1000: { slidesPerView: 2 } },\n keyboard: { enabled: true },\n });\n});\n<\/script>\n\n\n<p class=\"wp-block-paragraph\">Read More: <a href=\"https:\/\/www.scaler.com\/blog\/data-scientist-vs-machine-learning-engineer\/\">Data Scientist Vs Machine Learning Engineer<\/a><\/p>\n\n\n<p class=\"wp-block-paragraph\">While there is some overlap between these roles, Machine Learning Engineers generally sit closer to software engineering. Their goal is not just to create accurate models but to ensure those models can be deployed, monitored, and used effectively in real-world applications.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\">Looking for a guided path to becoming an ML Engineer? Do check out: <a href=\"https:\/\/www.scaler.com\/ai-machine-learning-course\/\">Advanced AI & Machine Learning Course with Agentic AI<\/a>.<\/p>\n\n\n<!-- scaler-insert:agentic_ai_banner -->\n\n<link href=\"https:\/\/fonts.googleapis.com\" rel=\"preconnect\"\/>\n<link crossorigin=\"\" href=\"https:\/\/fonts.gstatic.com\" rel=\"preconnect\"\/>\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Inter:wght@400;500;600;700;800&display=swap\" rel=\"stylesheet\"\/>\n<style>\n \/* Establishes a container-query context so the banner adapts to the width\n of wherever it is placed (blog column, sidebar, phone) \u2014 not the viewport. *\/\n .genai_banner_root {\n container-type: inline-size;\n width: 100%;\n max-width: 100%;\n }\n\n .genai_banner_container {\n --genai-banner-img: 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\"); \/* REPLACE-IMAGE *\/\n position: relative;\n display: flex;\n align-items: stretch;\n box-sizing: border-box;\n min-height: 340px;\n background: #FFFFFF;\n border: 1px solid #EEF0F2;\n border-radius: 16px;\n overflow: hidden;\n font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;\n }\n .genai_banner_container * { box-sizing: border-box; }\n\n \/* ---- Right-side course visual (sits behind the fade) ---- *\/\n .genai_banner_media {\n position: absolute;\n top: 0;\n right: 0;\n width: 52%;\n height: 100%;\n background-image: var(--genai-banner-img);\n background-size: cover;\n background-position: center center;\n background-repeat: no-repeat;\n }\n .genai_banner_fade {\n position: absolute;\n inset: 0;\n background: linear-gradient(to right, #FFFFFF 0%, rgba(255,255,255,0.88) 16%, rgba(255,255,255,0.45) 40%, rgba(255,255,255,0) 68%);\n }\n\n \/* ---- Left-side content ---- *\/\n .genai_banner_content {\n position: relative;\n z-index: 1;\n width: 54%;\n padding: 42px 40px 42px 52px;\n display: flex;\n flex-direction: column;\n justify-content: center;\n }\n .genai_banner_title {\n margin: 0 0 12px;\n font-size: 38px;\n font-weight: 800;\n line-height: 1.14;\n letter-spacing: -0.02em;\n color: #0D1117;\n }\n .genai_banner_title_hl { color: #BE1558; }\n .genai_banner_desc {\n margin: 0 0 24px;\n max-width: 440px;\n font-size: 15px;\n font-weight: 400;\n line-height: 1.6;\n color: #6B7280;\n }\n\n .genai_banner_cta_row {\n display: flex;\n align-items: center;\n gap: 20px;\n margin-bottom: 26px;\n flex-wrap: wrap;\n }\n .genai_banner_btn {\n display: inline-flex;\n align-items: center;\n gap: 8px;\n padding: 12px 24px;\n background: #BE1558;\n border: none;\n border-radius: 8px;\n font-size: 15px;\n font-weight: 700;\n line-height: 1;\n color: #FFFFFF !important;\n text-decoration: none;\n white-space: nowrap;\n transition: background 0.15s ease;\n }\n .genai_banner_btn:hover { background: #9E1049; }\n .genai_banner_btn svg { display: block; }\n\n .genai_banner_rating {\n display: flex;\n align-items: center;\n gap: 6px;\n font-size: 14px;\n line-height: 1;\n }\n .genai_banner_rating .star { color: #F59E0B; font-weight: 700; }\n .genai_banner_rating .muted { color: #9CA3AF; }\n\n .genai_banner_highlights {\n display: flex;\n gap: 22px;\n flex-wrap: nowrap;\n max-width: 470px;\n }\n .genai_banner_hl {\n display: flex;\n align-items: center;\n gap: 10px;\n flex: 1 1 0;\n min-width: 0;\n }\n .genai_banner_hl .ic {\n width: 34px;\n height: 34px;\n flex-shrink: 0;\n border-radius: 9px;\n background: #FAE8EF;\n display: flex;\n align-items: center;\n justify-content: center;\n }\n .genai_banner_hl .ic svg { display: block; }\n .genai_banner_hl .lbl { font-size: 11px; color: #9CA3AF; margin-bottom: 2px; }\n .genai_banner_hl .val { font-size: 13px; color: #0D1117; font-weight: 700; line-height: 1.2; }\n .genai_banner_hl .v-short { display: none; }\n\n \/* ---- Compact \/ mobile layout ----\n PRIMARY trigger = container width: the banner switches to the stacked\n mobile UI whenever its own box is narrower than 860px \u2014 so it responds\n to the blog column \/ sidebar \/ phone it is dropped into, not the browser\n viewport. FALLBACK trigger = viewport width (<=768px), so phones still\n get the mobile UI in older browsers that don't support container queries.\n Both blocks apply the exact same rules. *\/\n @container (max-width: 860px) {\n .genai_banner_container { flex-direction: column; min-height: 0; }\n .genai_banner_media { position: static; order: -1; width: 100%; height: 190px; background-position: center 18%; }\n .genai_banner_fade { display: none; }\n .genai_banner_content { width: 100%; padding: 26px 22px 24px; }\n .genai_banner_title { font-size: 25px; margin-bottom: 10px; }\n .genai_banner_desc { font-size: 13.5px; margin-bottom: 20px; max-width: none; }\n .genai_banner_cta_row { flex-direction: column; align-items: stretch; gap: 12px; margin-bottom: 22px; }\n .genai_banner_btn { width: 100%; justify-content: center; }\n .genai_banner_rating { justify-content: center; }\n .genai_banner_highlights { display: grid; grid-template-columns: repeat(3, 1fr); gap: 0; max-width: none; border: 1px solid #EFEFEF; border-radius: 10px; background: #FAFAFA; overflow: hidden; }\n .genai_banner_hl { gap: 8px; padding: 12px 8px; border-right: 1px solid #EFEFEF; }\n .genai_banner_hl .ic { width: 28px; height: 28px; border-radius: 7px; }\n .genai_banner_hl .ic svg { width: 15px; height: 15px; }\n .genai_banner_hl .lbl { font-size: 9.5px; }\n .genai_banner_hl .val { font-size: 11.5px; }\n .genai_banner_hl .val { max-width: none; }\n .genai_banner_hl:last-child { border-right: none; }\n .genai_banner_hl .v-full { display: none; }\n .genai_banner_hl .v-short { display: inline; }\n }\n\n @media (max-width: 768px) {\n .genai_banner_container { flex-direction: column; min-height: 0; }\n .genai_banner_media { position: static; order: -1; width: 100%; height: 190px; background-position: center 18%; }\n .genai_banner_fade { display: none; }\n .genai_banner_content { width: 100%; padding: 26px 22px 24px; }\n .genai_banner_title { font-size: 25px; margin-bottom: 10px; }\n .genai_banner_desc { font-size: 13.5px; margin-bottom: 20px; max-width: none; }\n .genai_banner_cta_row { flex-direction: column; align-items: stretch; gap: 12px; margin-bottom: 22px; }\n .genai_banner_btn { width: 100%; justify-content: center; }\n .genai_banner_rating { justify-content: center; }\n .genai_banner_highlights { display: grid; grid-template-columns: repeat(3, 1fr); gap: 0; max-width: none; border: 1px solid #EFEFEF; border-radius: 10px; background: #FAFAFA; overflow: hidden; }\n .genai_banner_hl { gap: 8px; padding: 12px 8px; border-right: 1px solid #EFEFEF; }\n .genai_banner_hl .ic { width: 28px; height: 28px; border-radius: 7px; }\n .genai_banner_hl .ic svg { width: 15px; height: 15px; }\n .genai_banner_hl .lbl { font-size: 9.5px; }\n .genai_banner_hl .val { font-size: 11.5px; }\n .genai_banner_hl .val { max-width: none; }\n .genai_banner_hl:last-child { border-right: none; }\n .genai_banner_hl .v-full { display: none; }\n .genai_banner_hl .v-short { display: inline; }\n }\n<\/style>\n<div class=\"genai_banner_root\">\n<div class=\"genai_banner_container\">\n<div class=\"genai_banner_media\"><\/div>\n<div class=\"genai_banner_fade\"><\/div>\n<div class=\"genai_banner_content\">\n<h2 class=\"genai_banner_title\"><span class=\"ez-toc-section\" id=\"free-agentic-ai-course-with-certification\"><\/span>\n Free Agentic AI Course<br\/>\n<span class=\"genai_banner_title_hl\">with Certification<\/span>\n<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"genai_banner_desc\">\n Learn LLMs, prompt engineering, RAG & agentic AI \u2014 hands-on.\n Earn an industry-recognised certificate at zero cost.\n <\/p>\n<div class=\"genai_banner_cta_row\">\n<a class=\"genai_banner_btn\" href=\"https:\/\/www.scaler.com\/topics\/course\/agentic-ai\/\" id=\"genai_banner_btn\">\n Start Learning for Free\n <svg aria-hidden=\"true\" fill=\"none\" height=\"15\" viewbox=\"0 0 14 14\" width=\"15\">\n<path d=\"M2.5 7h9M8 3.5l3.5 3.5L8 10.5\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"1.5\"><\/path>\n<\/svg>\n<\/a>\n<div class=\"genai_banner_rating\">\n<span class=\"star\">\u2605 4.8<\/span>\n<span class=\"muted\">\u00b7 1,002 enrolled<\/span>\n<\/div>\n<\/div>\n<div class=\"genai_banner_highlights\">\n<div class=\"genai_banner_hl\">\n<div class=\"ic\">\n<svg aria-hidden=\"true\" fill=\"none\" height=\"18\" viewbox=\"0 0 24 24\" width=\"18\">\n<path d=\"M12 4 2 9l10 5 8-4v6\" stroke=\"#9E1049\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"1.7\"><\/path>\n<path d=\"M6 12v4c0 1.1 2.7 2.5 6 2.5s6-1.4 6-2.5v-4\" stroke=\"#9E1049\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"1.7\"><\/path>\n<\/svg>\n<\/div>\n<div>\n<div class=\"lbl\">Certificate<\/div>\n<div class=\"val\"><span class=\"v-full\">Industry-recognised<\/span><span class=\"v-short\">Included<\/span><\/div>\n<\/div>\n<\/div>\n<div class=\"genai_banner_hl\">\n<div class=\"ic\">\n<svg aria-hidden=\"true\" fill=\"none\" height=\"18\" viewbox=\"0 0 24 24\" width=\"18\">\n<circle cx=\"12\" cy=\"12\" r=\"8.5\" stroke=\"#9E1049\" stroke-width=\"1.7\"><\/circle>\n<path d=\"M12 7.5V12l3 2\" stroke=\"#9E1049\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"1.7\"><\/path>\n<\/svg>\n<\/div>\n<div>\n<div class=\"lbl\">Duration<\/div>\n<div class=\"val\"><span class=\"v-full\">1h 9m \u00b7 7 Modules<\/span><span class=\"v-short\">7 Modules<\/span><\/div>\n<\/div>\n<\/div>\n<div class=\"genai_banner_hl\">\n<div class=\"ic\">\n<svg aria-hidden=\"true\" fill=\"none\" height=\"18\" viewbox=\"0 0 24 24\" width=\"18\">\n<rect fill=\"#9E1049\" height=\"6\" rx=\"1\" width=\"3.4\" x=\"4\" y=\"14\"><\/rect>\n<rect fill=\"#9E1049\" height=\"10\" rx=\"1\" width=\"3.4\" x=\"10.3\" y=\"10\"><\/rect>\n<rect fill=\"#9E1049\" height=\"14\" rx=\"1\" width=\"3.4\" x=\"16.6\" y=\"6\"><\/rect>\n<\/svg>\n<\/div>\n<div>\n<div class=\"lbl\">Level<\/div>\n<div class=\"val\"><span class=\"v-full\">Beginner-friendly<\/span><span class=\"v-short\">Beginner<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<script>\n (function () {\n function initScalerGenAIBanner() {\n var pathParts = location.pathname.split('\/').filter(Boolean);\n var currentSlug = pathParts.length > 0 ? pathParts[pathParts.length - 1] : 'homepage';\n var url = 'https:\/\/www.scaler.com\/topics\/course\/agentic-ai\/'\n + '?utm_source=blog'\n + '&utm_medium=agentic_ai'\n + '&utm_content=' + currentSlug;\n var btns = document.querySelectorAll('.genai_banner_btn');\n for (var i = 0; i < btns.length; i++) { btns[i].href = url; }\n }\n if (document.readyState === 'loading') {\n document.addEventListener('DOMContentLoaded', initScalerGenAIBanner);\n } else {\n initScalerGenAIBanner();\n }\n })();\n<\/script>\n\n<!-- \/scaler-insert:agentic_ai_banner -->\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"ml-engineer-roadmap-2026-at-a-glance-phase-overview\"><\/span><strong>ML Engineer Roadmap 2026 at a Glance (Phase Overview)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">The common question asked by many budding engineers is: how to become a machine learning engineer? While there is no single path into the field, all successful ML engineers tend to follow a certain sequence in which they begin from math and Python basics to finally reach machine learning and deep learning.<\/p>\n\n\n<p class=\"wp-block-paragraph\">The following ml engineer roadmap outlines the key phases, tools, and projects that can help you build practical ML engineering skills.\u00a0<\/p>\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Phase\u00a0<\/strong><\/td><td><strong>Key Skills\u00a0<\/strong><\/td><td><strong>Tools & Technologies\u00a0<\/strong><\/td><td><strong>Suggested Project\u00a0<\/strong><\/td><\/tr><tr><td>Phase 1: Foundations\u00a0<\/td><td>Python, Linear Algebra, Probability, Statistics\u00a0<\/td><td>Python, NumPy, Pandas, Jupyter Notebook\u00a0<\/td><td>Data Analysis Project\u00a0<\/td><\/tr><tr><td>Phase 2: Core Machine Learning\u00a0<\/td><td>Supervised Learning, Unsupervised Learning, Feature Engineering, Model Evaluation\u00a0<\/td><td>Scikit-learn, Pandas, Matplotlib\u00a0<\/td><td>End-to-End ML Model\u00a0<\/td><\/tr><tr><td>Phase 3: Deep Learning\u00a0<\/td><td>Neural Networks, CNNs, RNNs\u00a0<\/td><td>TensorFlow, PyTorch\u00a0<\/td><td>Image or Text Classification Project\u00a0<\/td><\/tr><tr><td>Phase 4: MLOps & Deployment\u00a0<\/td><td>Model Serving, Monitoring, Pipelines, Versioning\u00a0<\/td><td>Docker, FastAPI, MLflow, Git\u00a0<\/td><td>Deploy a Machine Learning API\u00a0<\/td><\/tr><tr><td>Phase 5: Generative AI & LLMs\u00a0<\/td><td>Prompt Engineering, RAG, Fine-Tuning Concepts\u00a0<\/td><td>Hugging Face, LangChain, Vector Databases\u00a0<\/td><td>LLM-Powered Application\u00a0<\/td><\/tr><tr><td>Phase 6: Portfolio & Career Preparation\u00a0<\/td><td>System Design, Project Documentation, Interview Preparation\u00a0<\/td><td>GitHub, Kaggle, Cloud Platforms\u00a0<\/td><td>Production-Ready ML Portfolio\u00a0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n<p class=\"wp-block-paragraph\">Read More: <a href=\"https:\/\/www.scaler.com\/blog\/machine-learning-roadmap\/\">Machine Learning Roadmap for 2026<\/a>\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\">Although the time frame might differ depending upon your experience, the sequence presented in this machine learning roadmap stays quite constant: having a solid foundation, acquiring knowledge about machine learning, deploying, and moving towards advanced topics like LLMs and generative AI.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Also, check out: <a href=\"https:\/\/www.scaler.com\/academy\/\">Modern Software & AI Engineering Course<\/a><\/p>\n\n<meta charset=\"UTF-8\">\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n\n <!-- Source Sans Pro (topics font) -->\n <link href=\"https:\/\/fonts.googleapis.com\/css2?family=Source+Sans+3:wght@400;600;700&display=swap\" rel=\"stylesheet\">\n <link rel=\"stylesheet\" href=\"https:\/\/cdn.jsdelivr.net\/npm\/swiper@11\/swiper-bundle.min.css\">\n <script src=\"https:\/\/cdn.jsdelivr.net\/npm\/swiper@11\/swiper-bundle.min.js\"><\/script>\n\n <style>\n :root {\n \/* topics design tokens (variables.scss) *\/\n --scaler-primary: #005bb3; \/* primary-color-80 *\/\n --scaler-primary-30: #8acaff; \/* primary-color-30 *\/\n --scaler-brand-blue: #255aad;\n --scaler-live: #ee001d; \/* accent-v5-60 *\/\n --scaler-live-bg: #ffe6e9; \/* accent-v5-10 *\/\n --scaler-card-bg: #ffffff; \/* neutral-scale-0 *\/\n --scaler-surface: #f4f6f9; \/* neutral-scale-2 *\/\n --scaler-text-primary: #1a2c47; \/* neutral-scale-12 *\/\n --scaler-text-secondary: #61738e; \/* neutral-scale-9 *\/\n --scaler-border: #d6dee5; \/* neutral-scale-4 *\/\n --scaler-radius: 16px;\n --scaler-radius-sm: 8px;\n --scaler-shadow: 0 8px 16px 0 rgba(50, 71, 102, 0.16);\n }\n\n .scaler-events-carousel * { box-sizing: border-box; }\n\n .scaler-events-carousel {\n font-family: \"Source Sans 3\", \"Source Sans Pro\", \"Roboto\", Arial, sans-serif;\n padding: 24px;\n position: relative;\n width: 100%;\n }\n .scaler-events-carousel__inner {\n max-width: 1000px;\n margin: 0 auto;\n position: relative;\n width: 100%;\n }\n\n \/* Header \u2014 calendar icon + \"Live Masterclasses\" *\/\n .scaler-events-header {\n display: flex;\n align-items: center;\n gap: 8px;\n margin-bottom: 8px;\n padding: 8px 0;\n }\n .scaler-events-header__icon { display: inline-flex; color: var(--scaler-text-primary); }\n .scaler-events-header__icon svg { width: 24px; height: 24px; }\n .scaler-events-header__title {\n font-size: 18px;\n font-weight: 700;\n color: var(--scaler-text-primary);\n line-height: 1.3;\n margin: 0;\n }\n\n \/* Swiper wrap (holds side arrows) *\/\n .scaler-events-swiper-wrap { position: relative; }\n .scaler-events-carousel .swiper { width: 100%; padding: 4px; }\n .scaler-event-swiper .swiper-slide {\n width: 296px; \/* topics card_container width *\/\n height: auto;\n display: flex;\n }\n\n \/* Event Card \u2014 matches topics EventCard *\/\n .scaler-event-card {\n background: var(--scaler-card-bg);\n border: 1px solid var(--scaler-border);\n border-radius: var(--scaler-radius);\n padding: 16px;\n display: flex;\n flex-direction: column;\n height: 100%;\n width: 100%;\n cursor: pointer;\n }\n\n \/* Header row: headshot + title\/name *\/\n .scaler-event-card__header { display: flex; align-items: flex-start; }\n .scaler-event-card__image-wrapper {\n position: relative;\n width: 88px;\n height: 88px;\n min-width: 88px;\n border-radius: var(--scaler-radius-sm);\n overflow: hidden;\n background: var(--scaler-primary-30);\n }\n .scaler-event-card__image {\n position: absolute;\n top: 0; left: 0;\n width: 100%; height: 100%;\n object-fit: cover;\n }\n \/* attendee-count footer (default) *\/\n .scaler-event-card__img-footer {\n position: absolute;\n left: 0; right: 0; bottom: 0;\n display: flex;\n align-items: center;\n justify-content: center;\n gap: 4px;\n padding: 1px 8px;\n background: var(--scaler-surface);\n color: var(--scaler-text-primary);\n font-size: 13px;\n line-height: 22px;\n }\n .scaler-event-card__img-footer svg { width: 14px; height: 14px; }\n \/* live chip (shown when status === current) *\/\n .scaler-event-card__live-badge {\n position: absolute;\n left: 0; right: 0; bottom: 0;\n display: flex;\n align-items: center;\n justify-content: center;\n gap: 5px;\n padding: 1px 8px;\n background: var(--scaler-live-bg);\n color: var(--scaler-live);\n font-size: 12px;\n line-height: 22px;\n text-transform: uppercase;\n letter-spacing: 0.18em;\n }\n .scaler-event-card__live-badge::before {\n content: \"\";\n width: 6px; height: 6px;\n background: var(--scaler-live);\n border-radius: 50%;\n }\n .scaler-event-card__text { margin-left: 16px; min-width: 0; }\n .scaler-event-card__title {\n font-size: 20px;\n font-weight: 600;\n color: var(--scaler-text-primary);\n margin: 0;\n line-height: 1.4;\n display: -webkit-box;\n -webkit-line-clamp: 2;\n -webkit-box-orient: vertical;\n overflow: hidden;\n }\n .scaler-event-card__speaker {\n margin-top: 8px;\n font-size: 14px;\n line-height: 1.4;\n color: var(--scaler-text-primary);\n }\n\n \/* Takeaways *\/\n .scaler-event-card__takeaways {\n margin-top: 12px;\n min-height: 50px;\n max-height: 50px;\n overflow: hidden;\n }\n .scaler-event-card__takeaway-item {\n display: flex;\n align-items: flex-start;\n gap: 6px;\n }\n .scaler-event-card__dot {\n width: 4px; height: 4px;\n min-width: 4px;\n border-radius: 50%;\n background: var(--scaler-text-secondary);\n margin-top: 11px;\n }\n .scaler-event-card__takeaway-text {\n flex: 1;\n min-width: 0;\n font-size: 14px;\n line-height: 24px;\n color: var(--scaler-text-primary);\n white-space: nowrap;\n overflow: hidden;\n text-overflow: ellipsis;\n }\n .scaler-event-card__knowmore,\n .scaler-event-card__knowmore:link,\n .scaler-event-card__knowmore:visited {\n flex-shrink: 0;\n font-size: 14px;\n line-height: 24px;\n color: var(--scaler-primary) !important;\n text-decoration: none;\n white-space: nowrap;\n }\n .scaler-event-card__knowmore:hover { text-decoration: underline; }\n\n \/* Date + duration *\/\n .scaler-event-card__meta {\n display: flex;\n align-items: center;\n justify-content: space-between;\n margin-top: 20px;\n font-size: 13px;\n line-height: 24px;\n color: var(--scaler-text-primary);\n }\n .scaler-event-card__duration {\n display: flex;\n align-items: center;\n gap: 4px;\n }\n .scaler-event-card__duration svg { width: 15px; height: 15px; }\n\n .scaler-event-card__spacer { flex-grow: 1; min-height: 4px; }\n\n \/* CTA \u2014 outlined \"Register with 1-Click\" *\/\n .scaler-event-card__cta,\n .scaler-event-card__cta:link,\n .scaler-event-card__cta:visited {\n display: flex;\n align-items: center;\n justify-content: center;\n width: 100%;\n margin-top: 16px;\n padding: 8px;\n background: transparent;\n color: var(--scaler-primary) !important;\n font-family: inherit;\n font-size: 14px;\n font-weight: 600;\n line-height: 24px;\n text-decoration: none;\n border: 1px solid var(--scaler-primary);\n border-radius: var(--scaler-radius-sm);\n cursor: pointer;\n transition: background 0.2s ease, color 0.2s ease;\n }\n .scaler-event-card__cta:hover,\n .scaler-event-card__cta:focus {\n background: var(--scaler-primary);\n color: #fff !important;\n }\n\n \/* Side navigation arrows *\/\n .scaler-events-nav__btn {\n position: absolute !important;\n top: 50% !important;\n transform: translateY(-50%) !important;\n z-index: 2;\n width: 46px !important;\n height: 46px !important;\n min-width: 46px;\n display: flex !important;\n align-items: center;\n justify-content: center;\n padding: 0 !important;\n background: var(--scaler-card-bg) !important;\n border: none !important;\n border-radius: var(--scaler-radius-sm) !important;\n box-shadow: var(--scaler-shadow) !important;\n color: var(--scaler-text-secondary) !important;\n cursor: pointer;\n transition: opacity 0.2s ease, visibility 0.2s ease;\n }\n .scaler-nav-prev { left: 8px !important; }\n .scaler-nav-next { right: 8px !important; }\n .scaler-events-nav__btn svg {\n width: 20px !important;\n height: 20px !important;\n fill: var(--scaler-text-secondary) !important;\n }\n .scaler-events-nav__btn.swiper-button-disabled {\n opacity: 0;\n visibility: hidden;\n pointer-events: none;\n }\n\n \/* View All Events *\/\n .scaler-events-viewall,\n .scaler-events-viewall:link,\n .scaler-events-viewall:visited {\n display: flex;\n align-items: center;\n justify-content: center;\n gap: 6px;\n margin-top: 12px;\n font-size: 14px;\n font-weight: 600;\n color: var(--scaler-brand-blue) !important;\n text-decoration: none;\n }\n .scaler-events-viewall:hover { text-decoration: underline; }\n .scaler-events-viewall svg { width: 16px; height: 16px; fill: var(--scaler-brand-blue); }\n\n \/* hide swiper defaults *\/\n .scaler-events-pagination { display: none; }\n .scaler-events-carousel .swiper-button-prev,\n .scaler-events-carousel .swiper-button-next { display: none; }\n\n \/* Skeleton & Empty States *\/\n .scaler-event-card--skeleton { pointer-events: none; }\n .scaler-event-card--skeleton .scaler-event-card__image-wrapper,\n .scaler-event-card--skeleton .scaler-event-card__title,\n .scaler-event-card--skeleton .scaler-event-card__speaker,\n .scaler-event-card--skeleton .scaler-event-card__takeaways,\n .scaler-event-card--skeleton .scaler-event-card__meta,\n .scaler-event-card--skeleton .scaler-event-card__cta {\n background: linear-gradient(90deg, var(--scaler-border) 25%, var(--scaler-surface) 50%, var(--scaler-border) 75%);\n background-size: 200% 100%;\n animation: shimmer 1.5s infinite;\n color: transparent !important;\n border-color: transparent !important;\n border-radius: 4px;\n }\n .scaler-event-card--skeleton .scaler-event-card__title { min-height: 44px; }\n .scaler-event-card--skeleton .scaler-event-card__speaker { min-height: 16px; }\n .scaler-event-card--skeleton .scaler-event-card__meta { min-height: 24px; }\n .scaler-event-card--skeleton .scaler-event-card__cta { min-height: 40px; }\n .scaler-event-card--skeleton .scaler-event-card__image,\n .scaler-event-card--skeleton .scaler-event-card__img-footer,\n .scaler-event-card--skeleton .scaler-event-card__live-badge { display: none; }\n\n @keyframes shimmer {\n 0% { background-position: 200% 0; }\n 100% { background-position: -200% 0; }\n }\n\n .scaler-events-empty {\n text-align: center;\n padding: 40px 20px;\n color: var(--scaler-text-secondary);\n font-size: 15px;\n }\n\n @media (max-width: 768px) {\n .scaler-events-carousel { padding: 16px; }\n .scaler-event-swiper .swiper-slide { width: calc(100vw - 52px); }\n .scaler-events-nav__btn { display: none; }\n }\n <\/style>\n\n\n\n <div class=\"scaler-events-carousel js-scaler-carousel\">\n\n <template class=\"js-event-card-template\">\n <div class=\"swiper-slide\">\n <article class=\"scaler-event-card\">\n <div class=\"scaler-event-card__header\">\n <div class=\"scaler-event-card__image-wrapper\">\n <img decoding=\"async\" src=\"\" alt=\"\" class=\"scaler-event-card__image\" loading=\"lazy\">\n <div class=\"scaler-event-card__img-footer\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M11.199 7.957c-3.086 0-5.588 2.502-5.588 5.588s2.502 5.588 5.588 5.588c3.086 0 5.588-2.502 5.588-5.588s-2.502-5.588-5.588-5.588zM3.611 13.545c0-4.191 3.397-7.588 7.588-7.588s7.588 3.397 7.588 7.588c0 4.191-3.397 7.588-7.588 7.588s-7.588-3.397-7.588-7.588z\"\/><path d=\"M21.090 6.369h0.003c1.989 0 3.897 0.79 5.303 2.197s2.197 3.314 2.197 5.303-0.79 3.897-2.197 5.303c-1.406 1.407-3.314 2.197-5.303 2.197-0.552 0-1-0.448-1-1s0.448-1 1-1c1.459 0 2.858-0.579 3.889-1.611s1.611-2.43 1.611-3.889c0-1.459-0.58-2.858-1.611-3.889s-2.429-1.611-3.888-1.611c-0.507 0.002-1.013 0.070-1.502 0.203-0.533 0.145-1.082-0.17-1.227-0.703s0.17-1.082 0.703-1.227c0.659-0.179 1.339-0.27 2.021-0.272z\"\/><path d=\"M10.906 21.364c-1.605 0-3.186 0.386-4.61 1.126s-2.649 1.811-3.572 3.124c-0.318 0.452-0.941 0.561-1.393 0.243s-0.561-0.941-0.243-1.393c1.107-1.576 2.577-2.862 4.286-3.749s3.606-1.351 5.532-1.351 3.823 0.463 5.532 1.351c1.709 0.888 3.179 2.174 4.286 3.749 0.318 0.452 0.209 1.076-0.243 1.393s-1.076 0.209-1.393-0.243c-0.923-1.313-2.148-2.385-3.572-3.124s-3.005-1.126-4.61-1.126z\"\/><\/svg>\n <span class=\"js-event-count\"><\/span>\n <\/div>\n <div class=\"scaler-event-card__live-badge\" style=\"display: none;\">Live<\/div>\n <\/div>\n <div class=\"scaler-event-card__text\">\n <h3 class=\"scaler-event-card__title\"><\/h3>\n <div class=\"scaler-event-card__speaker js-event-speaker\"><\/div>\n <\/div>\n <\/div>\n\n <div class=\"scaler-event-card__takeaways js-event-takeaways\"><\/div>\n\n <div class=\"scaler-event-card__spacer\"><\/div>\n\n <div class=\"scaler-event-card__meta\">\n <span class=\"js-event-date\"><\/span>\n <span class=\"scaler-event-card__duration\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M16 6.333c6.443 0 11.667 5.223 11.667 11.667s-5.223 11.667-11.667 11.667c-6.443 0-11.667-5.223-11.667-11.667v0c0.008-6.44 5.226-11.659 11.666-11.667h0.001zM16 28.333c5.707 0 10.333-4.626 10.333-10.333s-4.626-10.333-10.333-10.333c-5.707 0-10.333 4.626-10.333 10.333v0c0.007 5.704 4.629 10.326 10.333 10.333h0.001z\"\/><path d=\"M16 18.667c-0 0-0.001 0-0.001 0-0.184 0-0.35-0.074-0.471-0.195v0c-0.121-0.121-0.195-0.287-0.195-0.471s0.075-0.351 0.195-0.471l4.951-4.952c0.121-0.121 0.287-0.195 0.471-0.195s0.351 0.075 0.471 0.195v0c0.121 0.121 0.195 0.287 0.195 0.471s-0.075 0.351-0.195 0.471l-4.949 4.951c-0.121 0.121-0.288 0.196-0.472 0.196v0z\"\/><path d=\"M19 3.667h-6c-0.368 0-0.667-0.298-0.667-0.667v0c0-0.368 0.298-0.667 0.667-0.667v0h6c0.368 0 0.667 0.298 0.667 0.667v0c0 0.368-0.298 0.667-0.667 0.667v0z\"\/><\/svg>\n <span class=\"js-event-duration\"><\/span>\n <\/span>\n <\/div>\n\n <a href=\"#\" class=\"scaler-event-card__cta js-event-cta\">Register with 1-Click<\/a>\n <\/article>\n <\/div>\n <\/template>\n\n <div class=\"scaler-events-carousel__inner\">\n <header class=\"scaler-events-header\">\n <span class=\"scaler-events-header__icon\">\n <svg fill=\"currentColor\" viewBox=\"0 0 33 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M6.406 6.8c-0.11 0-0.2 0.090-0.2 0.2v20c0 0.11 0.090 0.2 0.2 0.2h20c0.11 0 0.2-0.090 0.2-0.2v-20c0-0.11-0.090-0.2-0.2-0.2h-20zM4.606 7c0-0.994 0.806-1.8 1.8-1.8h20c0.994 0 1.8 0.806 1.8 1.8v20c0 0.994-0.806 1.8-1.8 1.8h-20c-0.994 0-1.8-0.806-1.8-1.8v-20z\"\/><path d=\"M22.406 3.2c0.442 0 0.8 0.358 0.8 0.8v4c0 0.442-0.358 0.8-0.8 0.8s-0.8-0.358-0.8-0.8v-4c0-0.442 0.358-0.8 0.8-0.8z\"\/><path d=\"M10.406 3.2c0.442 0 0.8 0.358 0.8 0.8v4c0 0.442-0.358 0.8-0.8 0.8s-0.8-0.358-0.8-0.8v-4c0-0.442 0.358-0.8 0.8-0.8z\"\/><path d=\"M4.606 12c0-0.442 0.358-0.8 0.8-0.8h22c0.442 0 0.8 0.358 0.8 0.8s-0.358 0.8-0.8 0.8h-22c-0.442 0-0.8-0.358-0.8-0.8z\"\/><path d=\"M21.488 16.451c0.303 0.322 0.288 0.828-0.034 1.131l-5.838 5.5c-0.309 0.291-0.791 0.29-1.099-0.002l-3.162-3c-0.321-0.304-0.334-0.81-0.030-1.131s0.81-0.334 1.131-0.030l2.614 2.48 5.287-4.981c0.322-0.303 0.828-0.288 1.131 0.034z\"\/><\/svg>\n <\/span>\n <h2 class=\"scaler-events-header__title\"><span class=\"ez-toc-section\" id=\"live-masterclasses\"><\/span>Live Masterclasses<span class=\"ez-toc-section-end\"><\/span><\/h2>\n <\/header>\n\n <div class=\"scaler-events-swiper-wrap\">\n <div class=\"swiper scaler-event-swiper\">\n <div class=\"swiper-wrapper scaler-events-wrapper\"><\/div>\n <div class=\"swiper-pagination scaler-events-pagination\"><\/div>\n <\/div>\n\n <button class=\"scaler-events-nav__btn scaler-nav-prev\" aria-label=\"Previous slide\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"transform: rotate(-90deg);\"><path d=\"M5.313 16l10.688-10.688 10.688 10.688-1.938 1.875-7.438-7.438v16.25h-2.625v-16.25l-7.5 7.438z\"\/><\/svg>\n <\/button>\n <button class=\"scaler-events-nav__btn scaler-nav-next\" aria-label=\"Next slide\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"transform: rotate(90deg);\"><path d=\"M5.313 16l10.688-10.688 10.688 10.688-1.938 1.875-7.438-7.438v16.25h-2.625v-16.25l-7.5 7.438z\"\/><\/svg>\n <\/button>\n <\/div>\n\n <a class=\"scaler-events-viewall\" href=\"https:\/\/www.scaler.com\/events\/\">\n <span>View All Events<\/span>\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"transform: rotate(90deg);\"><path d=\"M5.313 16l10.688-10.688 10.688 10.688-1.938 1.875-7.438-7.438v16.25h-2.625v-16.25l-7.5 7.438z\"\/><\/svg>\n <\/a>\n <\/div>\n <\/div>\n\n <script>\n document.addEventListener(\"DOMContentLoaded\", () => {\n\n const monthNames = [\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"];\n\n function formatTime(st) {\n const t = new Date(st);\n const date = t.getDate();\n const month = monthNames[t.getMonth()];\n const year = t.getFullYear();\n const h = t.getHours();\n const m = String(t.getMinutes()).padStart(2, \"0\");\n let time;\n if (h === 0) time = `12:${m} AM`;\n else if (h === 12) time = `12:${m} PM`;\n else if (h > 12) time = `${h - 12}:${m} PM`;\n else time = `${h}:${m} AM`;\n return `${date} ${month} ${year} | ${time}`;\n }\n\n const carouselInstances = document.querySelectorAll('.js-scaler-carousel');\n\n carouselInstances.forEach(container => {\n\n if(container.dataset.initialized === \"true\") return;\n container.dataset.initialized = \"true\";\n\n const swiperElement = container.querySelector(\".scaler-event-swiper\");\n const swiperWrapper = container.querySelector(\".scaler-events-wrapper\");\n const template = container.querySelector(\".js-event-card-template\");\n const nextBtn = container.querySelector(\".scaler-nav-next\");\n const prevBtn = container.querySelector(\".scaler-nav-prev\");\n const paginationEl = container.querySelector(\".scaler-events-pagination\");\n\n if (!swiperWrapper || !template) {\n console.error(\"Scaler Carousel: Missing required elements inside container\");\n return;\n }\n\n const swiper = new Swiper(swiperElement, {\n slidesPerView: \"auto\",\n spaceBetween: 16,\n grabCursor: true,\n observer: true,\n observeParents: true,\n pagination: {\n el: paginationEl,\n clickable: true,\n dynamicBullets: true\n },\n navigation: {\n nextEl: nextBtn,\n prevEl: prevBtn\n },\n });\n\n function showSkeletons(count = 4) {\n swiperWrapper.innerHTML = \"\";\n for (let i = 0; i < count; i++) {\n const clone = template.content.cloneNode(true);\n const card = clone.querySelector(\".scaler-event-card\");\n card.classList.add(\"scaler-event-card--skeleton\");\n swiperWrapper.appendChild(clone);\n }\n swiper.update();\n }\n\n function renderEvents(events) {\n swiperWrapper.innerHTML = \"\";\n\n if (events.length === 0) {\n swiperWrapper.innerHTML = `<div class=\"scaler-events-empty\">No upcoming masterclasses found.<\/div>`;\n return;\n }\n\n const pathParts = location.pathname.split(\"\/\").filter(Boolean);\n const currentSlug = pathParts.length > 0 ? pathParts[pathParts.length - 1] : \"homepage\";\n\n events.forEach(event => {\n const attr = event.attributes;\n const cd = attr.custom_data || {};\n const clone = template.content.cloneNode(true);\n const joinUrl = `\/event\/${attr.slug}\/?utm_source=blog&utm_medium=master_class&utm_content=${currentSlug}`;\n\n \/\/ Instructor headshot\n const instructor = (cd.instructors && cd.instructors[0]) || {};\n const img = clone.querySelector(\".scaler-event-card__image\");\n img.src = instructor.media_url || attr.image_url ||\n \"https:\/\/images.unsplash.com\/photo-1531891437562-4301cf35b7e4?w=200&h=200&fit=crop\";\n img.alt = instructor.name || attr.instructor_name || attr.title;\n\n \/\/ Title + speaker\n clone.querySelector(\".scaler-event-card__title\").textContent = attr.title;\n clone.querySelector(\".js-event-speaker\").textContent = instructor.name || attr.instructor_name || \"\";\n\n \/\/ Live chip vs attendee count\n const isLive = attr.status === \"current\";\n const footer = clone.querySelector(\".scaler-event-card__img-footer\");\n const liveBadge = clone.querySelector(\".scaler-event-card__live-badge\");\n if (isLive) {\n footer.style.display = \"none\";\n liveBadge.style.display = \"flex\";\n liveBadge.textContent = \"Live\";\n } else if (attr.registration_count) {\n clone.querySelector(\".js-event-count\").textContent = attr.registration_count;\n } else {\n footer.style.display = \"none\";\n }\n\n \/\/ Takeaways (up to 2, Know More on the last)\n const takeaways = (cd.takeaways || []).slice(0, 2);\n const listEl = clone.querySelector(\".js-event-takeaways\");\n listEl.innerHTML = \"\";\n takeaways.forEach((t, idx) => {\n const item = document.createElement(\"div\");\n item.className = \"scaler-event-card__takeaway-item\";\n const dot = document.createElement(\"span\");\n dot.className = \"scaler-event-card__dot\";\n const txt = document.createElement(\"span\");\n txt.className = \"scaler-event-card__takeaway-text\";\n txt.textContent = t;\n item.appendChild(dot);\n item.appendChild(txt);\n if (idx === takeaways.length - 1) {\n const km = document.createElement(\"a\");\n km.className = \"scaler-event-card__knowmore\";\n km.textContent = \"Know More\";\n km.href = joinUrl;\n item.appendChild(km);\n }\n listEl.appendChild(item);\n });\n\n \/\/ Date + duration\n clone.querySelector(\".js-event-date\").textContent = formatTime(attr.start_time);\n let hrs = \"\";\n if (attr.duration) {\n hrs = (attr.duration \/ 60).toFixed(2);\n } else if (attr.end_time) {\n hrs = (Math.abs(new Date(attr.start_time) - new Date(attr.end_time)) \/ 3600000).toFixed(2);\n }\n clone.querySelector(\".js-event-duration\").textContent = hrs ? `${hrs} Hrs` : \"\";\n\n \/\/ CTA\n clone.querySelector(\".js-event-cta\").href = joinUrl;\n\n swiperWrapper.appendChild(clone);\n });\n\n swiper.update();\n swiper.slideTo(0);\n }\n\n async function fetchEvents() {\n try {\n showSkeletons();\n const res = await fetch(\n \"https:\/\/www.scaler.com\/api\/v4\/events?event_type[]=company&distributor=scaler&type=upcoming&serializer_mode=L2&limit=8&program[]=software_development&program[]=data_science&program[]=devops&program[]=ai_ml\"\n );\n const json = await res.json();\n const events = json.data || [];\n renderEvents(events);\n } catch (error) {\n console.error(\"Failed to load events:\", error);\n if(swiperWrapper) swiperWrapper.innerHTML = `<div class=\"scaler-events-empty\">Failed to load events.<\/div>`;\n }\n }\n\n fetchEvents();\n });\n });\n <\/script>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"phase-1-foundations-maths-statistics-python\"><\/span><strong>Phase 1: Foundations Maths, Statistics & Python<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">While many potential ML engineers are interested in neural networks and LLMs, the best engineers will always be those who start at the beginning. Mathematics, statistics, and Python are among the most important ML engineer skills, forming the foundation of almost every machine learning workflow.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Focus Areas:\u00a0<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Mathematics & Statistics<\/strong><\/p>\n\n\n<ul class=\"wp-block-list\">\n<li>Linear Algebra<\/li>\n\n\n<li>Probability<\/li>\n\n\n<li>Statistics<\/li>\n\n\n<li>Probability Distributions<\/li>\n\n\n<li>Hypothesis Testing<\/li>\n\n\n<li>Basic Calculus and Optimization<\/li>\n<\/ul>\n\n\n<p class=\"wp-block-paragraph\"><strong>Python<\/strong><\/p>\n\n\n<ul class=\"wp-block-list\">\n<li>Core <a href=\"https:\/\/www.scaler.com\/topics\/python\/\">Python<\/a> Programming<\/li>\n\n\n<li>NumPy<\/li>\n\n\n<li>Pandas<\/li>\n\n\n<li>Data Visualization<\/li>\n\n\n<li>File Handling and APIs<\/li>\n\n\n<li>Jupyter Notebooks<\/li>\n<\/ul>\n\n\n<p class=\"wp-block-paragraph\"><strong>Are You Ready for Phase 2?<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\">Before moving to machine learning algorithms, make sure you can:<\/p>\n\n\n<ul class=\"wp-block-list\">\n<li>Analyze datasets using Python<\/li>\n\n\n<li>Work comfortably with NumPy and Pandas<\/li>\n\n\n<li>Understand vectors, matrices, and probability concepts<\/li>\n\n\n<li>Interpret basic statistical results<\/li>\n\n\n<li>Read and debug Python code<\/li>\n<\/ul>\n\n\n<p class=\"wp-block-paragraph\">A strong foundation in these areas will make it much easier to understand model training, evaluation, deep learning, and MLOps later in the roadmap.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Explore these topics in more detail with this <a href=\"https:\/\/www.scaler.com\/topics\/course\/python-for-data-science\/\">Free Data Science Course with Certificate<\/a>.<\/p>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"phase-2-core-machine-learning\"><\/span><strong>Phase 2: Core Machine Learning<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Phase two addresses the basics of machine learning every ML engineer should know. While a lot of beginners think that algorithms are important, machine learning projects that happen in reality might consist of many other aspects. Usually, understanding the data, picking features, and proper evaluation are more valuable for project success than replacing one algorithm with another.<\/p>\n\n\n<p class=\"wp-block-paragraph\">For example, let's consider a very basic project: a prediction of customer churn. You start with a data set, preprocess it, pick the necessary features, build a model, and finally check whether it gives useful predictions. If the outcome is not good, the best thing to do in this situation is probably not to pick a more complex algorithm.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Learn more for free: <a href=\"https:\/\/www.scaler.com\/topics\/machine-learning\/\">Machine Learning Tutorial<\/a>.<\/p>\n\n\n<p class=\"wp-block-paragraph\">During this stage, you should pay attention to such topics as <a href=\"https:\/\/www.scaler.com\/topics\/supervised-and-unsupervised-learning\/\">supervised and unsupervised learning<\/a>, feature engineering, model evaluation, and the Scikit-learn environment. The idea here is not to remember all the algorithms but to learn the entire workflow of machine learning projects.<\/p>\n\n\n<!DOCTYPE html>\n<html>\n <head>\n <title>Hello World!<\/title>\n <link rel=\"preconnect\" href=\"https:\/\/fonts.googleapis.com\">\n <link rel=\"preconnect\" href=\"https:\/\/fonts.gstatic.com\" crossorigin>\n <link href=\"https:\/\/fonts.googleapis.com\/css2?family=Lato:wght@400;600;700&display=swap\" rel=\"stylesheet\">\n <style>\n .iitr_banner_container {\n font-family: lato;\n display: flex;\n flex-direction: row;\n justify-content: space-between;\n border-radius: 16px;\n background: linear-gradient(88deg, #19000F 24.45%, #66003F 83.33%);\n position: relative;\n\n @media (max-width: 768px) {\n min-height: 450px;\n overflow: hidden;\n flex-direction: column;\n }\n }\n .iitr_banner_content {\n display: flex;\n flex-direction: column;\n align-items: flex-start;\n justify-content: center;\n padding: 20px;\n max-width: 50%;\n\n @media (max-width: 768px) {\n max-width: 100%;\n }\n }\n .iitr_banner_title {\n font-size: 24px;\n font-weight: bold;\n color: #FFFFFF;\n\n @media (max-width: 768px) {\n font-size: 20px;\n }\n }\n .iitr_banner_title_highlight {\n color: #FF0071;\n }\n .iitr_banner_subtitle {\n font-size: 14px;\n color: #FFFFFF;\n margin: 10px 0;\n }\n .iitr_banner_btn {\n display: flex;\n justify-content: center;\n align-items: center;\n padding: 8px 48px;\n background-color: #F8F9F9;\n border-radius: 8px;\n border: 1px solid #E3E8E8;\n font-size: 1.4rem;\n font-weight: 600;\n color: #0D3231;\n text-decoration: none;\n margin-top: 16px;\n\n @media (max-width: 768px) {\n padding: 8px 32px;\n }\n }\n .iitr_banner_image {\n position: absolute;\n bottom: 0;\n right: 0;\n\n @media (max-width: 768px) {\n right: auto;\n object-fit: cover;\n min-width: 100%\n }\n }\n .iitr_banner_image_logo {\n margin-bottom: 16px;\n \n @media (max-width: 768px) {\n width: 240px;\n }\n }\n\n \/* Responsive visibility utilities *\/\n .show-in-mobile {\n display: none;\n }\n .hide-in-mobile {\n display: block;\n }\n\n \/* Mobile breakpoint (768px and below) *\/\n @media (max-width: 768px) {\n .show-in-mobile {\n display: block;\n }\n .hide-in-mobile {\n display: none;\n }\n }\n <\/style>\n <\/head>\n <body>\n <div class=\"iitr_banner_container\">\n <div class=\"iitr_banner_content\">\n <img decoding=\"async\" src=\"https:\/\/d2beiqkhq929f0.cloudfront.net\/public_assets\/assets\/000\/176\/281\/original\/Frame_1430102419.svg?1769058073\" class=\"iitr_banner_image_logo\" \/>\n <div class=\"iitr_banner_title\">\n AI Engineering Course Advanced Certification by \n <span class=\"iitr_banner_title_highlight\">\n IIT-Roorkee CEC\n <\/span>\n <\/div>\n <div class=\"iitr_banner_subtitle\">\n A hands on AI engineering program covering Machine Learning, Generative AI, and LLMs - designed for working professionals & delivered by IIT Roorkee in collaboration with Scaler.\n <\/div>\n <a class=\"iitr_banner_btn\" href=\"#\" id=\"iitr_banner_btn\">Enrol Now<\/a>\n <\/div>\n <!-- Desktop Image -->\n <img decoding=\"async\" class=\"iitr_banner_image hide-in-mobile\" src=\"https:\/\/d2beiqkhq929f0.cloudfront.net\/public_assets\/assets\/000\/176\/282\/original\/iitr_2.svg?1769058132\" \/>\n <!-- Mobile Image -->\n <img decoding=\"async\" class=\"iitr_banner_image show-in-mobile\" src=\"https:\/\/d2beiqkhq929f0.cloudfront.net\/public_assets\/assets\/000\/176\/283\/original\/iitr_2_%281%29.svg?1769059469\" \/>\n <\/div>\n <script>\n document.addEventListener(\"DOMContentLoaded\", () => {\n const pathParts = location.pathname.split(\"\/\").filter(Boolean);\n const currentSlug = pathParts.length > 0 ? pathParts[pathParts.length - 1] : \"homepage\";\n const url = `https:\/\/www.scaler.com\/iit-roorkee-advanced-ai-engineering-course?utm_source=blog&utm_medium=iit_roorkee&utm_content=${currentSlug}`;\n const btns = document.querySelectorAll(\".iitr_banner_btn\");\n btns.forEach(btn => {\n btn.href = url;\n });\n });\n <\/script>\n <\/body>\n<\/html>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"phase-3-deep-learning-neural-networks\"><\/span><strong>Phase 3: Deep Learning & Neural Networks<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">While traditional machine learning methods require the design of effective features, <a href=\"https:\/\/www.scaler.com\/topics\/deep-learning\/\">deep learning<\/a> works in a completely different way, in that it enables the training of neural networks using raw data. This is what makes deep learning a core component of today\u2019s artificial intelligence applications like image recognition, voice processing, and generative AI.<\/p>\n\n\n<p class=\"wp-block-paragraph\">What You'll Learn:<\/p>\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Topic\u00a0<\/strong><\/td><td><strong>Why It Matters\u00a0<\/strong><\/td><\/tr><tr><td>Neural Networks\u00a0<\/td><td>Foundation of deep learning models\u00a0<\/td><\/tr><tr><td>CNNs\u00a0<\/td><td>Widely used for image and computer vision tasks\u00a0<\/td><\/tr><tr><td>RNNs\u00a0<\/td><td>Useful for sequential and time-series data\u00a0<\/td><\/tr><tr><td>TensorFlow\u00a0<\/td><td>Popular framework for building and training models\u00a0<\/td><\/tr><tr><td>PyTorch\u00a0<\/td><td>Widely used in research and production environments\u00a0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n<p class=\"wp-block-paragraph\">You can look into it in more detail with this <a href=\"https:\/\/www.scaler.com\/blog\/deep-learning-roadmap\/\">Deep Learning Roadmap 2026: Step-by-Step Learning Path<\/a>.<\/p>\n\n\n<p class=\"wp-block-paragraph\">As you progress through your deep learning journey, worry less about remembering mathematical equations and concentrate more on grasping how machines learn and why they suffer from overfitting. Doing small projects using TensorFlow or PyTorch will educate you much better than theoretical studies ever will.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Start your learning journey today with: <a href=\"https:\/\/www.scaler.com\/data-science-course\/\">Data Science & ML Course with AI Specialization<\/a>.<\/p>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"phase-4-mlops-model-deployment\"><\/span><strong>Phase 4: MLOps & Model Deployment<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Many machine learning projects never make it beyond a notebook. Building a model is only part of the job; real value comes from deploying that model, serving predictions reliably, and ensuring it continues to perform well over time. This is exactly where MLOps becomes essential.<\/p>\n\n\n<p class=\"wp-block-paragraph\">MLOps for beginners can be defined as the set of practices that help move machine learning from experimentation to production. Instead of focusing only on model accuracy, you'll learn how to manage the entire lifecycle of an ML system.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Key Areas to Focus On -<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Model Deployment:<\/strong> Serving trained models through APIs and applications.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Version Control:<\/strong> Tracking datasets, code changes, and model versions.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>ML Pipelines<\/strong>: Automating data preparation, training, testing, and deployment workflows.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Monitoring<\/strong>: Detecting performance issues, data drift, and model degradation after deployment.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Containerization & Cloud Platforms<\/strong>: Using tools such as Docker and cloud services to run ML workloads at scale.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Curious about career progression in ML? Check out: <a href=\"https:\/\/www.scaler.com\/blog\/machine-learning-career\/\">Machine Learning Career: A Comprehensive Guide<\/a><\/p>\n\n\n<p class=\"wp-block-paragraph\">A simple way to think about MLOps is this: A Data Scientist may build a model that works, but an ML Engineer makes sure that this model is deployable, monitorable, updatable, and reliable enough to run in production. With the increased complexity of machine learning systems, this skillset is now becoming an essential one.<\/p>\n\n\n<div style=\"text-align:center; margin:24px 0;\">\n<a href=\"https:\/\/www.scaler.com\/neovarsity\/v2\/?utm_source=blog&utm_medium=banner&utm_campaign=neovarsity\" rel=\"noopener\" target=\"_blank\">\n<img decoding=\"async\" alt=\"Scaler Neovarsity - Skip the GRE, Earn an Accredited US Master's While You Work\" src=\"https:\/\/scaler-blog-prod-wp-content.s3.ap-south-1.amazonaws.com\/wp-content\/uploads\/2026\/07\/14131216\/Frame-13-1-scaled.webp\" style=\"max-width:100%; height:auto; display:block; margin:0 auto; border-radius:8px;\"\/>\n<\/a>\n<\/div>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"phase-5-generative-ai-llms\"><\/span><strong>Phase 5: Generative AI & LLMs<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Where machine learning was the trendsetter in the previous decade, LLMs and Generative AI are leading the charge in the coming years. Not all modern AI solutions depend on the predictions made by machine learning techniques anymore. They make use of large language models in order to do searches, generate content, write code, offer support, and retrieve knowledge.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Rather than focusing merely on prompt engineering, today\u2019s ML engineers should think about LLM engineering, which requires a good understanding of how such models are used in real systems, how they can access external knowledge, and how to optimize them for particular tasks.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Key Areas to Explore<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Large Language Models (LLMs)<\/strong>: Understanding how modern language models work and where they are used.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Retrieval-Augmented Generation (RAG)<\/strong>: Combining LLMs with external knowledge sources to generate more accurate and context-aware responses.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Fine-Tuning<\/strong>: Adapting pre-trained models for domain-specific tasks and applications.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Inference & Deployment<\/strong>: Serving LLM-powered applications efficiently and reliably.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Evaluation & Monitoring<\/strong>: Measuring response quality, reliability, and performance in production environments.<\/p>\n\n\n<p class=\"wp-block-paragraph\">This phase does not involve becoming an AI research scientist. This phase involves learning how to develop, deploy, and maintain LLM applications. The more organizations move from experimenting to developing production AI systems, the more in demand skills involving working with RAG pipelines, model serving, and LLM deployments will be among Machine Learning Engineers.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Read More: <a href=\"https:\/\/www.scaler.com\/blog\/ai-engineer-roadmap-master-genai-llms-deep-learning\/\">AI Engineer Roadmap 2026<\/a><\/p>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"phase-6-build-an-ml-project-portfolio\"><\/span><strong>Phase 6: Build an ML Project Portfolio<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Portfolio becomes the best way of showing your competencies as an ML engineer. While studies and certificates are able to show that you know something, projects become the evidence that you are able to implement what you have learned. This is why machine learning projects must become an integral part of your educational process.<\/p>\n\n\n<p class=\"wp-block-paragraph\">A good approach is to build projects that gradually increase in complexity:\u00a0<\/p>\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Project Level\u00a0<\/strong><\/td><td><strong>Example Project\u00a0<\/strong><\/td><td><strong>Skills Demonstrated\u00a0<\/strong><\/td><\/tr><tr><td>Beginner\u00a0<\/td><td>House Price Prediction, Customer Churn Prediction\u00a0<\/td><td>Data Cleaning, EDA, Model Training, Evaluation\u00a0<\/td><\/tr><tr><td>Intermediate\u00a0<\/td><td>Recommendation System, Sales Forecasting Model\u00a0<\/td><td>Feature Engineering, Model Selection, Performance Optimization\u00a0<\/td><\/tr><tr><td>Advanced\u00a0<\/td><td>End-to-End ML Pipeline\u00a0<\/td><td>Data Processing, Automation, Model Deployment\u00a0<\/td><\/tr><tr><td>Production-Level\u00a0<\/td><td>Deployed ML Web Application\u00a0<\/td><td>APIs, MLOps, Monitoring, User-Facing Applications\u00a0<\/td><\/tr><tr><td>Modern AI\u00a0<\/td><td>RAG-Based Chatbot or LLM Application\u00a0<\/td><td>LLM Engineering, Retrieval Systems, Deployment\u00a0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n<p class=\"wp-block-paragraph\">When developing projects, pay attention to documentation, rather than just releasing your code. Describe the problem statement, your data pre-processing, models that were tested, and why you made those choices. Good documentation in a project may show the level of your engineering skills better than a repository full of notebooks.<\/p>\n\n\n<p class=\"wp-block-paragraph\">By the end of this machine learning engineer roadmap, you should have a portfolio that presents the complete machine learning workflow, from data analysis and model development to deployment and monitoring.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Looking for project ideas? Start here: <a href=\"https:\/\/www.scaler.com\/topics\/courses\/\">Free Programming and Coding Courses Online with Certificate<\/a>.<\/p>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"career-path-salary-for-ml-engineers-in-india\"><\/span><strong>Career Path & Salary for ML Engineers in India<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Machine Learning Engineering offers multiple career paths, ranging from traditional machine learning roles to emerging areas such as MLOps, Generative AI, and LLM-based systems. As your technical expertise grows, your responsibilities typically expand from building and evaluating models to designing and maintaining production-scale ML systems.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\">The progression in this field of work looks like this:\u00a0<\/p>\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Experience Level\u00a0<\/strong><\/td><td><strong>Typical Roles\u00a0<\/strong><\/td><\/tr><tr><td>Entry Level\u00a0<\/td><td>ML Engineer Intern, Junior ML Engineer, Data Analyst\u00a0<\/td><\/tr><tr><td>Early Career\u00a0<\/td><td>Machine Learning Engineer, Applied AI Engineer, Data Scientist\u00a0<\/td><\/tr><tr><td>Mid Level\u00a0<\/td><td>Senior ML Engineer, MLOps Engineer, AI Engineer\u00a0<\/td><\/tr><tr><td>Advanced\u00a0<\/td><td>Lead ML Engineer, Machine Learning Architect, AI Engineering Manager\u00a0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n<p class=\"wp-block-paragraph\">The ML engineer salary in India ranges from <a href=\"https:\/\/www.glassdoor.co.in\/Salaries\/machine-learning-engineer-salary-SRCH_KO0,25.htm\" target=\"_blank\" rel=\"noopener\">\u20b96L to \u20b915LPA<\/a>, which is determined based on parameters like technical capabilities, experience in working on projects, expertise in various domains, and knowledge about production systems. Those who possess good fundamentals in machine learning, software engineering, cloud computing, and MLOps usually get more chances as firms are increasingly looking to develop AI-powered products and services.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Although there may be variations in salary among different organizations and regions, the long-term career prospects usually depend on the capability of creating, deploying, and maintaining machine learning solutions.<\/p>\n\n\n<p class=\"wp-block-paragraph\">You can check the salary trends in detail here: <a href=\"https:\/\/www.scaler.com\/blog\/machine-learning-engineer-salary\/\">Machine Learning Engineer Salary in India 2025-26<\/a>\u00a0<\/p>\n\n<meta charset=\"UTF-8\">\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n\n <!-- Source Sans Pro (topics font) -->\n <link href=\"https:\/\/fonts.googleapis.com\/css2?family=Source+Sans+3:wght@400;600;700&display=swap\" rel=\"stylesheet\">\n <link 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js-course-link\" href=\"#\" target=\"_blank\" rel=\"noopener\">\n <img decoding=\"async\" class=\"scaler-course-card__image js-course-image\" src=\"\" alt=\"\" loading=\"lazy\">\n <div class=\"scaler-course-card__detail\">\n <div class=\"scaler-course-card__heading js-course-title\"><\/div>\n <div class=\"scaler-course-card__instructor js-course-instructor\"><\/div>\n <div class=\"scaler-course-card__desc js-course-desc\"><\/div>\n <div class=\"scaler-course-card__footer\">\n <span class=\"scaler-course-card__stat js-course-star\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M14.83 2.868c0.342-0.239 0.75-0.368 1.168-0.368s0.826 0.128 1.168 0.368c0.338 0.236 0.596 0.569 0.741 0.955l2.759 6.936c0.003 0.007 0.007 0.013 0.013 0.017s0.013 0.007 0.020 0.007l7.402 0.476c0.411 0.036 0.802 0.194 1.124 0.452s0.559 0.607 0.683 1 0.127 0.815 0.011 1.211c-0.116 0.396-0.347 0.748-0.664 1.013l-5.655 4.714c-0.013 0.011-0.022 0.025-0.028 0.040s-0.006 0.032-0.002 0.047l1.821 7.163c0.107 0.395 0.094 0.812-0.037 1.2-0.133 0.391-0.38 0.734-0.71 0.983s-0.727 0.393-1.14 0.413c-0.413 0.020-0.822-0.084-1.175-0.3l-0.015-0.009-6.307-4.005c-0.004-0.003-0.009-0.004-0.014-0.004s-0.009 0.001-0.013 0.004l-5.876 3.721c-0.389 0.235-0.839 0.347-1.292 0.323s-0.889-0.184-1.251-0.459c-0.361-0.275-0.632-0.652-0.777-1.082-0.143-0.426-0.157-0.885-0.038-1.319l1.684-6.629c0.004-0.016 0.003-0.033-0.002-0.049s-0.015-0.030-0.027-0.040l-5.653-4.714c-0.317-0.264-0.548-0.617-0.664-1.013s-0.112-0.817 0.011-1.211c0.124-0.394 0.361-0.742 0.683-1s0.713-0.416 1.124-0.452l0.023-0.002 7.38-0.476c0.007-0 0.014-0.003 0.020-0.007s0.010-0.010 0.013-0.017l0.008-0.020 2.746-6.913c0.145-0.386 0.403-0.719 0.741-0.956z\"\/><\/svg>\n <span class=\"js-course-star-val\"><\/span>\n <\/span>\n <span class=\"scaler-course-card__stat\">\n <img decoding=\"async\" src=\"https:\/\/d19zaobb0foqu6.cloudfront.net\/topics\/images\/user-check-dark.svg\" alt=\"Enrolled\" loading=\"lazy\">\n <span class=\"js-course-reg\"><\/span>\n <\/span>\n <\/div>\n <\/div>\n <\/a>\n <\/div>\n <\/template>\n\n <div class=\"scaler-courses__inner\">\n <div class=\"scaler-courses__header\">\n <span class=\"scaler-courses__header-icon\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M26.259 23.289h-20.518c-1.193 0-2.16-0.967-2.16-2.16v0-14.588c0-1.193 0.967-2.16 2.16-2.16v0h20.518c1.193 0 2.16 0.967 2.16 2.16v0 14.588c0 1.193-0.967 2.16-2.16 2.16v0zM5.741 5.501c-0.574 0-1.040 0.466-1.040 1.040v0 14.588c0 0.574 0.466 1.040 1.040 1.040v0h20.518c0.574 0 1.040-0.466 1.040-1.040v0-14.588c0-0.574-0.466-1.040-1.040-1.040v0z\"\/><path d=\"M19.764 27.619h-7.53c-0.309 0-0.56-0.251-0.56-0.56v0c0-0.309 0.251-0.56 0.56-0.56h7.53c0.309 0 0.56 0.251 0.56 0.56v0c0 0.309-0.251 0.56-0.56 0.56v0z\"\/><path d=\"M14.023 9.322c0.116 0 0.223 0.035 0.312 0.096l-0.002-0.001 5.93 3.953c0.151 0.102 0.249 0.272 0.249 0.466s-0.098 0.364-0.247 0.465l-0.002 0.001-5.93 3.953c-0.087 0.059-0.195 0.094-0.31 0.094-0.309 0-0.56-0.25-0.56-0.559v-7.906c0-0.309 0.251-0.56 0.56-0.56v0zM18.943 13.835l-4.36-2.906v5.813z\"\/><\/svg>\n <\/span>\n <h2 class=\"scaler-courses__title\"><span class=\"ez-toc-section\" id=\"free-courses-by-top-scaler-instructors\"><\/span>Free Courses by top Scaler instructors<span class=\"ez-toc-section-end\"><\/span><\/h2>\n <\/div>\n\n <div class=\"scaler-courses__swiper-wrap\">\n <div class=\"swiper scaler-courses-swiper\">\n <div class=\"swiper-wrapper js-courses-wrapper\"><\/div>\n <div class=\"swiper-pagination\"><\/div>\n <\/div>\n\n <button class=\"scaler-courses__nav scaler-courses__nav--prev js-courses-prev\" aria-label=\"Previous\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"transform: rotate(-90deg);\"><path d=\"M5.313 16l10.688-10.688 10.688 10.688-1.938 1.875-7.438-7.438v16.25h-2.625v-16.25l-7.5 7.438z\"\/><\/svg>\n <\/button>\n <button class=\"scaler-courses__nav scaler-courses__nav--next js-courses-next\" aria-label=\"Next\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"transform: rotate(90deg);\"><path d=\"M5.313 16l10.688-10.688 10.688 10.688-1.938 1.875-7.438-7.438v16.25h-2.625v-16.25l-7.5 7.438z\"\/><\/svg>\n <\/button>\n <\/div>\n <\/div>\n <\/div>\n\n <script>\n document.addEventListener(\"DOMContentLoaded\", () => {\n const EXTRA_COUNT_ADDED = 1000;\n\n \/\/ Mirrors getInstructorStar(): first token of the headline.\n function getInstructorStar(headline) {\n return (headline || \"\").toString().split(\" \")[0] || \"\";\n }\n\n document.querySelectorAll(\".js-scaler-courses\").forEach(container => {\n if (container.dataset.initialized === \"true\") return;\n container.dataset.initialized = \"true\";\n\n const swiperElement = container.querySelector(\".scaler-courses-swiper\");\n const wrapper = container.querySelector(\".js-courses-wrapper\");\n const template = container.querySelector(\".js-course-card-template\");\n const nextBtn = container.querySelector(\".js-courses-next\");\n const prevBtn = container.querySelector(\".js-courses-prev\");\n\n if (!wrapper || !template) return;\n\n const swiper = new Swiper(swiperElement, {\n slidesPerView: \"auto\",\n spaceBetween: 16,\n grabCursor: true,\n observer: true,\n observeParents: true,\n navigation: { nextEl: nextBtn, prevEl: prevBtn },\n });\n\n const pathParts = location.pathname.split(\"\/\").filter(Boolean);\n const currentSlug = pathParts.length > 0 ? pathParts[pathParts.length - 1] : \"homepage\";\n\n function showSkeletons(count = 4) {\n wrapper.innerHTML = \"\";\n for (let i = 0; i < count; i++) {\n const clone = template.content.cloneNode(true);\n clone.querySelector(\".scaler-course-card\").classList.add(\"scaler-course-card--skeleton\");\n wrapper.appendChild(clone);\n }\n swiper.update();\n }\n\n function renderCourses(courses) {\n wrapper.innerHTML = \"\";\n if (!courses.length) { container.style.display = \"none\"; return; }\n\n courses.forEach(item => {\n const a = item.attributes || {};\n const clone = template.content.cloneNode(true);\n const instructor = (a.instructors_data && a.instructors_data[0]) || {};\n\n clone.querySelector(\".js-course-link\").href =\n `https:\/\/www.scaler.com\/topics\/course\/${a.slug}\/?utm_source=blog&utm_medium=free_courses&utm_content=${currentSlug}`;\n\n const img = clone.querySelector(\".js-course-image\");\n img.src = a.cover_image_thumbnail || a.featured_image || \"\";\n img.alt = a.title || \"\";\n\n clone.querySelector(\".js-course-title\").textContent = a.title || \"\";\n\n const instrEl = clone.querySelector(\".js-course-instructor\");\n if (instructor.name) {\n instrEl.innerHTML = \"A Course by <b><\/b>\";\n instrEl.querySelector(\"b\").textContent = instructor.name;\n } else {\n instrEl.style.display = \"none\";\n }\n\n clone.querySelector(\".js-course-desc\").textContent = a.description || \"\";\n\n \/\/ Star\n const star = getInstructorStar(instructor.star_headline);\n const starWrap = clone.querySelector(\".js-course-star\");\n if (star && star !== \"0\") clone.querySelector(\".js-course-star-val\").textContent = star;\n else starWrap.style.display = \"none\";\n\n \/\/ Enrolled count (+1000 like topics)\n clone.querySelector(\".js-course-reg\").textContent =\n ((a.user_registration_count || 0) + EXTRA_COUNT_ADDED).toLocaleString(\"en-US\");\n\n wrapper.appendChild(clone);\n });\n\n swiper.update();\n swiper.slideTo(0);\n }\n\n async function fetchCourses() {\n try {\n showSkeletons();\n \/\/ Public same-origin endpoint (topics course search). Returns 6 free courses.\n const res = await fetch(\"\/topics\/api\/v1\/search\/courses\", {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application\/json\",\n \"Accept\": \"application\/json\",\n \"X-Requested-With\": \"XMLHttpRequest\",\n },\n body: JSON.stringify({\n filters: {\n q: \"\",\n page: { limit: 6, current_page: 1 },\n sort: { key: \"user_registration_count\", order: \"desc\" },\n filter_type: null,\n tags: [],\n program: [],\n level: [],\n category_type: [],\n },\n }),\n });\n const json = await res.json();\n const courses = (json && json.data) || [];\n renderCourses(courses);\n } catch (error) {\n console.error(\"Failed to load courses:\", error);\n container.style.display = \"none\";\n }\n }\n\n fetchCourses();\n });\n });\n <\/script>\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"how-to-get-your-first-ml-engineer-job\"><\/span><strong>How to Get Your First ML Engineer Job<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Understanding machine learning is one thing, but getting employers to understand how you can implement it in practical applications is quite another. Generally speaking, the best candidates are not those who merely possess certificates but rather use project work, experience, and portfolios to demonstrate their proficiency.<\/p>\n\n\n<p class=\"wp-block-paragraph\">To strengthen your ML engineer career path, focus on building evidence of your work:<\/p>\n\n\n<ul class=\"wp-block-list\">\n<li>Publish end-to-end machine learning projects on GitHub<\/li>\n\n\n<li>Participate in Kaggle competitions and dataset challenges<\/li>\n\n\n<li>Document your project approach, assumptions, and results<\/li>\n\n\n<li>Contribute to open-source ML or AI projects<\/li>\n\n\n<li>Build and deploy at least one production-ready ML application<\/li>\n\n\n<li>Practice coding, machine learning, and system design interviews<\/li>\n<\/ul>\n\n\n<p class=\"wp-block-paragraph\">When preparing for interviews, be ready to discuss more than just algorithms. Hiring managers often want to understand how you approached a problem, handled data quality issues, selected evaluation metrics, and made deployment decisions. Being able to explain your thought process is often just as important as building an accurate model.<\/p>\n\n\n<p class=\"wp-block-paragraph\">A strong portfolio, consistent project work, and a solid understanding of machine learning fundamentals can significantly improve your chances of landing your first role as an ML Engineer, even if you're transitioning from another domain.<\/p>\n\n\n<p class=\"wp-block-paragraph\">Interested in guided learning? Check out: <a href=\"https:\/\/www.scaler.com\/academy\/\">Modern Software & AI Engineering Course<\/a><\/p>\n\n<meta charset=\"UTF-8\">\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">\n\n <!-- Source Sans Pro (topics font) -->\n <link href=\"https:\/\/fonts.googleapis.com\/css2?family=Source+Sans+3:wght@400;600;700&display=swap\" rel=\"stylesheet\">\n <link rel=\"stylesheet\" href=\"https:\/\/cdn.jsdelivr.net\/npm\/swiper@11\/swiper-bundle.min.css\">\n <script src=\"https:\/\/cdn.jsdelivr.net\/npm\/swiper@11\/swiper-bundle.min.js\"><\/script>\n\n <style>\n :root {\n --ss-primary: #005bb3; \/* primary-color-80 *\/\n --ss-card-bg: #ffffff;\n --ss-border: #e6e6e6;\n --ss-quote-bg: #f6f6f6;\n --ss-text-dark: #1c1c1c;\n --ss-text-mid: #6b6b6b;\n --ss-text-muted: #9a9a9a;\n --ss-radius: 12px;\n --ss-radius-sm: 8px;\n --ss-shadow: 0 8px 16px 0 rgba(50, 71, 102, 0.16);\n }\n\n .scaler-ss * { box-sizing: border-box; }\n\n .scaler-ss {\n font-family: \"Source Sans 3\", \"Source Sans Pro\", \"Roboto\", Arial, sans-serif;\n padding: 24px;\n width: 100%;\n }\n .scaler-ss__inner {\n max-width: 1000px;\n margin: 0 auto;\n position: relative;\n width: 100%;\n }\n\n \/* Heading *\/\n .scaler-ss__heading {\n font-size: 26px;\n line-height: 34px;\n font-weight: 700;\n margin: 0 0 16px;\n text-align: center;\n color: var(--ss-text-dark);\n }\n\n \/* Swiper *\/\n .scaler-ss__swiper-wrap { position: relative; }\n .scaler-ss .swiper { width: 100%; padding: 4px; }\n .scaler-ss-swiper .swiper-slide {\n width: 300px; \/* topics card width *\/\n height: auto;\n display: flex;\n }\n\n \/* Card *\/\n .scaler-ss-card {\n display: flex;\n flex-direction: column;\n width: 100%;\n border: 1px solid var(--ss-border);\n border-radius: var(--ss-radius);\n overflow: hidden;\n background: var(--ss-card-bg);\n }\n\n .scaler-ss-card__hike {\n padding: 8px 12px;\n background: var(--ss-primary);\n color: #ffffff;\n font-size: 14px;\n font-weight: 700;\n text-align: center;\n letter-spacing: 0.4px;\n }\n\n .scaler-ss-card__body {\n display: flex;\n flex: 1 1 auto;\n flex-direction: column;\n gap: 12px;\n padding: 16px;\n }\n\n \/* Person *\/\n .scaler-ss-card__person {\n display: flex;\n align-items: center;\n gap: 10px;\n }\n .scaler-ss-card__avatar {\n width: 44px;\n height: 44px;\n min-width: 44px;\n border-radius: 50%;\n object-fit: cover;\n background: var(--ss-quote-bg);\n }\n .scaler-ss-card__name {\n font-size: 16px;\n font-weight: 700;\n line-height: 20px;\n color: var(--ss-text-dark);\n }\n .scaler-ss-card__city {\n font-size: 13px;\n line-height: 18px;\n color: var(--ss-text-mid);\n }\n\n \/* Before \/ Now transition *\/\n .scaler-ss-card__transition {\n display: flex;\n align-items: center;\n justify-content: space-between;\n gap: 8px;\n }\n .scaler-ss-card__col {\n flex: 1;\n min-width: 0;\n }\n .scaler-ss-card__col-label {\n font-size: 11px;\n font-weight: 600;\n letter-spacing: 0.4px;\n color: var(--ss-text-muted);\n margin-bottom: 2px;\n }\n .scaler-ss-card__col-role {\n font-size: 13px;\n line-height: 18px;\n color: var(--ss-text-mid);\n }\n .scaler-ss-card__col-company {\n font-size: 14px;\n font-weight: 700;\n line-height: 20px;\n color: var(--ss-text-dark);\n }\n .scaler-ss-card__company-logo {\n margin-top: 2px;\n max-width: 64px;\n max-height: 20px;\n width: auto;\n height: auto;\n object-fit: contain;\n display: block;\n }\n .scaler-ss-card__arrow {\n flex-shrink: 0;\n width: 28px;\n height: 8px;\n color: var(--ss-text-mid);\n fill: currentColor;\n }\n\n \/* Quote *\/\n .scaler-ss-card__quote {\n font-size: 13px;\n font-style: italic;\n line-height: 19px;\n color: var(--ss-text-mid);\n background: var(--ss-quote-bg);\n border-radius: var(--ss-radius-sm);\n padding: 8px 10px;\n }\n\n \/* View Profile *\/\n .scaler-ss-card__cta,\n .scaler-ss-card__cta:link,\n .scaler-ss-card__cta:visited {\n display: block;\n margin-top: auto;\n text-align: center;\n font-size: 14px;\n font-weight: 600;\n color: var(--ss-primary) !important;\n text-decoration: none;\n border: 1px solid var(--ss-primary);\n border-radius: var(--ss-radius-sm);\n padding: 9px 12px;\n cursor: pointer;\n transition: background 0.2s ease, color 0.2s ease;\n }\n .scaler-ss-card__cta:hover,\n .scaler-ss-card__cta:focus {\n background: var(--ss-primary);\n color: #ffffff !important;\n }\n\n \/* Side navigation arrows *\/\n .scaler-ss__nav {\n position: absolute !important;\n top: 50% !important;\n transform: translateY(-50%) !important;\n z-index: 2;\n width: 46px !important;\n height: 46px !important;\n min-width: 46px;\n display: flex !important;\n align-items: center;\n justify-content: center;\n padding: 0 !important;\n background: var(--ss-card-bg) !important;\n border: none !important;\n border-radius: var(--ss-radius-sm) !important;\n box-shadow: var(--ss-shadow) !important;\n color: #61738e !important;\n cursor: pointer;\n transition: opacity 0.2s ease, visibility 0.2s ease;\n }\n .scaler-ss__nav--prev { left: 8px !important; }\n .scaler-ss__nav--next { right: 8px !important; }\n .scaler-ss__nav svg {\n width: 20px !important;\n height: 20px !important;\n fill: #61738e !important;\n }\n .scaler-ss__nav.swiper-button-disabled {\n opacity: 0;\n visibility: hidden;\n pointer-events: none;\n }\n\n .scaler-ss .swiper-button-prev,\n .scaler-ss .swiper-button-next,\n .scaler-ss .swiper-pagination { display: none; }\n\n \/* Skeleton *\/\n .scaler-ss-card--skeleton { pointer-events: none; }\n .scaler-ss-card--skeleton .scaler-ss-card__hike,\n .scaler-ss-card--skeleton .scaler-ss-card__avatar,\n .scaler-ss-card--skeleton .scaler-ss-card__person-text,\n .scaler-ss-card--skeleton .scaler-ss-card__transition,\n .scaler-ss-card--skeleton .scaler-ss-card__quote,\n .scaler-ss-card--skeleton .scaler-ss-card__cta {\n background: linear-gradient(90deg, var(--ss-border) 25%, var(--ss-quote-bg) 50%, var(--ss-border) 75%);\n background-size: 200% 100%;\n animation: ss-shimmer 1.5s infinite;\n color: transparent !important;\n border-color: transparent !important;\n border-radius: 4px;\n }\n .scaler-ss-card--skeleton .scaler-ss-card__person-text { flex: 1; height: 32px; }\n .scaler-ss-card--skeleton .scaler-ss-card__transition { height: 56px; }\n .scaler-ss-card--skeleton .scaler-ss-card__quote { height: 48px; }\n .scaler-ss-card--skeleton .scaler-ss-card__cta { height: 38px; }\n\n @keyframes ss-shimmer {\n 0% { background-position: 200% 0; }\n 100% { background-position: -200% 0; }\n }\n\n @media (max-width: 768px) {\n .scaler-ss { padding: 16px; }\n .scaler-ss__heading { font-size: 22px; line-height: 30px; }\n .scaler-ss-swiper .swiper-slide { width: 270px; }\n .scaler-ss__nav { display: none !important; }\n }\n <\/style>\n\n\n\n <div class=\"scaler-ss js-scaler-ss\">\n\n <template class=\"js-ss-card-template\">\n <div class=\"swiper-slide\">\n <article class=\"scaler-ss-card\">\n <div class=\"scaler-ss-card__hike js-ss-hike\"><\/div>\n <div class=\"scaler-ss-card__body\">\n <div class=\"scaler-ss-card__person\">\n <img decoding=\"async\" class=\"scaler-ss-card__avatar js-ss-avatar\" src=\"\" alt=\"\" loading=\"lazy\">\n <div class=\"scaler-ss-card__person-text\">\n <div class=\"scaler-ss-card__name js-ss-name\"><\/div>\n <div class=\"scaler-ss-card__city js-ss-city\"><\/div>\n <\/div>\n <\/div>\n\n <div class=\"scaler-ss-card__transition\">\n <div class=\"scaler-ss-card__col\">\n <div class=\"scaler-ss-card__col-label\">BEFORE:<\/div>\n <div class=\"scaler-ss-card__col-role js-ss-before-role\"><\/div>\n <div class=\"scaler-ss-card__col-company js-ss-before-company\"><\/div>\n <\/div>\n <svg class=\"scaler-ss-card__arrow\" viewBox=\"0 0 32 8\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M31.3882 4.35355C31.5835 4.15829 31.5835 3.84171 31.3882 3.64645L28.2062 0.464466C28.011 0.269204 27.6944 0.269204 27.4991 0.464466C27.3039 0.659728 27.3039 0.976311 27.4991 1.17157L30.3276 4L27.4991 6.82843C27.3039 7.02369 27.3039 7.34027 27.4991 7.53553C27.6944 7.7308 28.011 7.7308 28.2062 7.53553L31.3882 4.35355ZM0.034668 4.5H31.0347V3.5H0.034668V4.5Z\"><\/path><\/svg>\n <div class=\"scaler-ss-card__col\">\n <div class=\"scaler-ss-card__col-label\">NOW:<\/div>\n <div class=\"scaler-ss-card__col-role js-ss-now-role\"><\/div>\n <div class=\"js-ss-now-company\"><\/div>\n <\/div>\n <\/div>\n\n <div class=\"scaler-ss-card__quote js-ss-quote\"><\/div>\n\n <a class=\"scaler-ss-card__cta js-ss-cta\" href=\"#\" target=\"_blank\" rel=\"noopener\">View Profile<\/a>\n <\/div>\n <\/article>\n <\/div>\n <\/template>\n\n <div class=\"scaler-ss__inner\">\n <h2 class=\"scaler-ss__heading\"><span class=\"ez-toc-section\" id=\"scaler-alumni-and-their-success-stories\"><\/span>Scaler Alumni and Their Success Stories<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n <div class=\"scaler-ss__swiper-wrap\">\n <div class=\"swiper scaler-ss-swiper\">\n <div class=\"swiper-wrapper js-ss-wrapper\"><\/div>\n <\/div>\n\n <button class=\"scaler-ss__nav scaler-ss__nav--prev js-ss-prev\" aria-label=\"Previous\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"transform: rotate(-90deg);\"><path d=\"M5.313 16l10.688-10.688 10.688 10.688-1.938 1.875-7.438-7.438v16.25h-2.625v-16.25l-7.5 7.438z\"><\/path><\/svg>\n <\/button>\n <button class=\"scaler-ss__nav scaler-ss__nav--next js-ss-next\" aria-label=\"Next\">\n <svg fill=\"currentColor\" viewBox=\"0 0 32 32\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"transform: rotate(90deg);\"><path d=\"M5.313 16l10.688-10.688 10.688 10.688-1.938 1.875-7.438-7.438v16.25h-2.625v-16.25l-7.5 7.438z\"><\/path><\/svg>\n <\/button>\n <\/div>\n <\/div>\n <\/div>\n\n <script>\n document.addEventListener(\"DOMContentLoaded\", () => {\n\n const ASSET_CDN = \"https:\/\/d2beiqkhq929f0.cloudfront.net\/public_assets\/assets\";\n const AVATAR_FALLBACK =\n \"data:image\/svg+xml,%3Csvg xmlns='http:\/\/www.w3.org\/2000\/svg' width='44' height='44' viewBox='0 0 44 44'%3E%3Ccircle cx='22' cy='22' r='22' fill='%23e6e6e6'\/%3E%3Ccircle cx='22' cy='17' r='7' fill='%23b9b9b9'\/%3E%3Cpath d='M8 40c0-8 6.3-13 14-13s14 5 14 13' fill='%23b9b9b9'\/%3E%3C\/svg%3E\";\n\n \/\/ Mirrors buildAssetUrl(): pass through absolute urls, else build the CDN url.\n function buildAssetUrl(raw) {\n if (!raw) return \"\";\n if (String(raw).startsWith(\"http\")) return raw;\n return `${ASSET_CDN}\/${raw}\/original`;\n }\n\n const instances = document.querySelectorAll(\".js-scaler-ss\");\n\n instances.forEach(container => {\n if (container.dataset.initialized === \"true\") return;\n container.dataset.initialized = \"true\";\n\n const swiperElement = container.querySelector(\".scaler-ss-swiper\");\n const wrapper = container.querySelector(\".js-ss-wrapper\");\n const template = container.querySelector(\".js-ss-card-template\");\n const nextBtn = container.querySelector(\".js-ss-next\");\n const prevBtn = container.querySelector(\".js-ss-prev\");\n\n if (!wrapper || !template) {\n console.error(\"Scaler Success Stories: missing required elements\");\n return;\n }\n\n const swiper = new Swiper(swiperElement, {\n slidesPerView: \"auto\",\n spaceBetween: 16,\n grabCursor: true,\n observer: true,\n observeParents: true,\n navigation: { nextEl: nextBtn, prevEl: prevBtn },\n });\n\n const pathParts = location.pathname.split(\"\/\").filter(Boolean);\n const currentSlug = pathParts.length > 0 ? pathParts[pathParts.length - 1] : \"homepage\";\n const profileUrl =\n `https:\/\/www.scaler.com\/review\/?utm_source=blog&utm_medium=success_stories&utm_content=${currentSlug}`;\n\n function showSkeletons(count = 4) {\n wrapper.innerHTML = \"\";\n for (let i = 0; i < count; i++) {\n const clone = template.content.cloneNode(true);\n clone.querySelector(\".scaler-ss-card\").classList.add(\"scaler-ss-card--skeleton\");\n wrapper.appendChild(clone);\n }\n swiper.update();\n }\n\n function renderStories(stories) {\n wrapper.innerHTML = \"\";\n if (!stories.length) {\n container.style.display = \"none\"; \/\/ match topics: render nothing when empty\n return;\n }\n\n stories.forEach(story => {\n const a = story.attributes || {};\n const clone = template.content.cloneNode(true);\n\n const hike = String(a.growth || \"\").replace(\"%\", \"\").trim() || \"150\";\n clone.querySelector(\".js-ss-hike\").textContent = `${hike}% HIKE`;\n\n \/\/ Avatar\n const avatar = buildAssetUrl(a.image_url) || a.generated_thumbnail_url || \"\";\n const img = clone.querySelector(\".js-ss-avatar\");\n img.src = avatar || AVATAR_FALLBACK;\n img.alt = a.name || \"Scaler alumnus\";\n img.onerror = function () { this.onerror = null; this.src = AVATAR_FALLBACK; };\n\n clone.querySelector(\".js-ss-name\").textContent = a.name || \"\";\n const cityEl = clone.querySelector(\".js-ss-city\");\n if (a.city) cityEl.textContent = a.city; else cityEl.style.display = \"none\";\n\n \/\/ BEFORE\n clone.querySelector(\".js-ss-before-role\").textContent = a.pre_scaler_role || a.pre_academy_company || \"\";\n const beforeCompany = clone.querySelector(\".js-ss-before-company\");\n if (a.pre_academy_company) beforeCompany.textContent = a.pre_academy_company;\n else beforeCompany.style.display = \"none\";\n\n \/\/ NOW\n clone.querySelector(\".js-ss-now-role\").textContent = a.role || \"\";\n const nowCompanyBox = clone.querySelector(\".js-ss-now-company\");\n const companyLogo = buildAssetUrl(a.company_logo_url);\n if (companyLogo) {\n const logo = document.createElement(\"img\");\n logo.className = \"scaler-ss-card__company-logo\";\n logo.src = companyLogo;\n logo.alt = a.post_academy_company || \"company\";\n logo.loading = \"lazy\";\n logo.onerror = function () {\n this.onerror = null;\n this.replaceWith(Object.assign(document.createElement(\"div\"), {\n className: \"scaler-ss-card__col-company\",\n textContent: a.post_academy_company || \"\",\n }));\n };\n nowCompanyBox.appendChild(logo);\n } else if (a.post_academy_company) {\n nowCompanyBox.className = \"scaler-ss-card__col-company\";\n nowCompanyBox.textContent = a.post_academy_company;\n }\n\n \/\/ Quote (clip to 110 chars like topics)\n const quoteEl = clone.querySelector(\".js-ss-quote\");\n quoteEl.textContent = `\u201c${String(a.content).slice(0, 110)}\u2026\u201d`;\n\n \/\/ View Profile\n clone.querySelector(\".js-ss-cta\").href = profileUrl;\n\n wrapper.appendChild(clone);\n });\n\n swiper.update();\n swiper.slideTo(0);\n }\n\n async function fetchStories() {\n try {\n showSkeletons();\n \/\/ Same-origin POST on www.scaler.com (the blog canonical host).\n \/\/ The endpoint only returns JSON when the Referer is a \/topics\/ page\n \/\/ (a soft anti-hotlinking gate); a \/blog\/ referer gets a Turbolinks\n \/\/ redirect. Since blog + topics are the same origin, we set the\n \/\/ fetch referrer to a topics URL so the server serves the data.\n const res = await fetch(\"\/success-stories\/testimonials\", {\n method: \"POST\",\n credentials: \"include\",\n referrer: \"https:\/\/www.scaler.com\/topics\/\",\n referrerPolicy: \"unsafe-url\",\n headers: {\n \"Content-Type\": \"application\/json\",\n \"Accept\": \"application\/json\",\n \"X-Requested-With\": \"XMLHttpRequest\",\n },\n \/\/ q:{} => all programs (no program filter)\n body: JSON.stringify({\n page_number: 1,\n per_page: 12,\n sort_by: \"eligible_for_qna\",\n new_quick_filters: true,\n quick_filter: [],\n q: {},\n }),\n });\n const json = await res.json();\n const all = (json && json.data && json.data.data) || [];\n \/\/ Only show stories that carry a testimonial quote (matches topics).\n const withQuote = all.filter(s => s.attributes && s.attributes.content);\n renderStories(withQuote);\n } catch (error) {\n console.error(\"Failed to load success stories:\", error);\n container.style.display = \"none\";\n }\n }\n\n fetchStories();\n });\n });\n <\/script>\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"faqs\"><\/span><strong>FAQs<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\"><strong>Q1. How long does it take to become an ML engineer?<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\">It depends on your background. Candidates with programming and mathematics fundamentals can often become job-ready within 6-12 months, while complete beginners may take 12\u201318 months, depending on the time they can dedicate to learning and projects.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Q2. Do I need a strong maths background for ML engineering?<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\">You don't need advanced mathematics, but a solid understanding of linear algebra, probability, and statistics is important for understanding how machine learning models work.<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Q3. What's the difference between an ML engineer and a data scientist?<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\">Data scientists primarily focus on data analysis, experimentation, and insights, while ML engineers focus on building, deploying, and maintaining machine learning systems in production.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Q4. Which is more important, ML theory or MLOps?<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\">Both are important; ML theory helps you build better models, while MLOps helps you deploy and manage them in real-world environments.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Q5. Can I become an ML engineer without a CS degree?<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\">Yes, many ML engineers come from diverse backgrounds. Strong projects, practical skills, and a solid portfolio often matter more than a specific degree.\u00a0<\/p>\n\n\n<p class=\"wp-block-paragraph\"><strong>Q6. How important are LLMs and generative AI for ML engineers in 2026?<\/strong><\/p>\n\n\n<p class=\"wp-block-paragraph\">They are becoming increasingly important. Understanding concepts such as RAG, fine-tuning, model deployment, and LLM-powered applications can be a valuable addition to your ML skill set.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A few years back, the ability to build an ML model was good enough to set you apart from the crowd. Now, companies expect their ML engineers to perform many tasks with big data, including training models, putting them into production, monitoring their performance, and developing applications on top of LLMs and Generative AI. The […]<\/p>\n","protected":false},"author":210,"featured_media":12894,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[333,37],"tags":[303,438,437],"class_list":["post-12893","post","type-post","status-publish","format-standard","has-post-thumbnail","category-roadmap","category-artificial-intelligence-machine-learning","tag-machine-learning","tag-ml-engineer-roadmap","tag-roadmpa"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/posts\/12893","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/users\/210"}],"replies":[{"embeddable":true,"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/comments?post=12893"}],"version-history":[{"count":3,"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/posts\/12893\/revisions"}],"predecessor-version":[{"id":14203,"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/posts\/12893\/revisions\/14203"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/media\/12894"}],"wp:attachment":[{"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/media?parent=12893"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/categories?post=12893"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.scaler.com\/blog\/wp-json\/wp\/v2\/tags?post=12893"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}