<h2>About this course</h2>
<p>Made With ML is a comprehensive guide to building production-ready machine learning systems—from design through deployment. Created by Goku Mohandas, this course bridges the gap between academic ML theory and real-world engineering, covering the full <a href="/topics/mlops">MLOps</a> lifecycle that powers AI in industry.</p>

<h2>What you'll learn</h2>
<ul>
<li>Design machine learning systems with proper data pipelines, feature engineering, and model selection strategies</li>
<li>Build and train models using industry-standard frameworks and best practices for reproducibility</li>
<li>Deploy ML models to production with containerization, versioning, and monitoring</li>
<li>Implement continuous integration and continuous deployment (CI/CD) for machine learning workflows</li>
<li>Manage model performance in production, including retraining and drift detection</li>
<li>Use version control and experiment tracking to organize ML projects professionally</li>
<li>Understand the operational challenges that distinguish ML in production from academic projects</li>
</ul>

<h2>Who this is for</h2>
<p>This course is ideal if you have some programming experience and want to move beyond toy models to understand how real companies build and maintain AI systems at scale. You'll gain practical engineering skills that employers actively seek.</p>
<ul>
<li>Software engineers and <a href="/for/developers">developers</a> — level up your ML engineering skills and become a more competitive candidate for AI-focused roles</li>
<li><a href="/for/data-scientists">Data scientists</a> — learn the engineering practices that turn research notebooks into reliable production systems</li>
</ul>

<h2>Prerequisites</h2>
<p>You should have foundational Python programming experience and basic familiarity with machine learning concepts (supervised learning, training/testing splits). This is not a beginner's introduction to ML—it assumes you already know the fundamentals and want to learn deployment and operations.</p>

<h2>Why this matters for Indian learners</h2>
<p>India's AI and tech sector is rapidly expanding, and MLOps skills are in high demand across Bangalore, Hyderabad, and Mumbai tech hubs. Companies like Flipkart, Amazon India, and homegrown startups are hiring ML engineers who can not just train models but ship them reliably. This course teaches the exact engineering discipline that separates junior data scientists from senior ML engineers—skills that command higher salaries and lead to architect-level roles.</p>

<h2>Frequently asked questions</h2>
<h3>Is this course really free?</h3>
<p>Yes. Made With ML is entirely free—no hidden paywalls or premium tiers required.</p>
<h3>How long will it take to complete?</h3>
<p>The course is structured for 40 hours of learning. If you dedicate 5–7 hours per week, you can complete it in 6–8 weeks. Some sections involve hands-on coding projects, so pace yourself to let concepts sink in.</p>
<h3>Will I get a certificate?</h3>
<p>This course does not offer a completion certificate. However, the real value lies in the practical skills and portfolio work you'll build—those speak louder to employers than a certificate badge.</p>

Made With ML

Goku Mohandas's Made With ML — design, develop, deploy production ML systems. Excellent MLOps resource.

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