Machine Learning in Hindi (CodeBasics)

About this course

This Hindi-language machine learning playlist from CodeBasics breaks down ML concepts in a way that actually makes sense—no English jargon walls, no leaps in logic. Dhaval Patel is known in the Indian developer community for clear explanations paired with hands-on coding examples, making this course ideal if you learn better in Hindi and want to avoid the friction of English-medium technical content.

What you'll learn

• Foundational ML concepts: what machine learning is, how it differs from traditional programming, and where it fits in real-world projects
• Supervised learning algorithms: linear regression, logistic regression, and decision trees—with practical coding walkthroughs
• Data preprocessing: cleaning, normalizing, and preparing datasets so your models actually work
• Model evaluation: how to measure accuracy, prevent overfitting, and choose between competing models
• Hands-on Python coding: writing ML pipelines using libraries like scikit-learn and pandas
• End-to-end project approach: taking a raw problem from idea to a trained, tested model
• Common pitfalls and debugging: troubleshooting that goes beyond theory, grounded in real mistakes

Who this is for

You're a learner who's comfortable with basic Python and wants to level up into machine learning—but you've been intimidated by English-heavy courses or textbooks. This course meets you where you are, in Hindi, with practical examples you can immediately code along with.

• Students and freshers — build a concrete ML portfolio project before your first job interview, giving you a real edge in competitive hiring
• Self-taught developers — bridge the gap from coding tutorials to applied machine learning with step-by-step guidance in your native language

Prerequisites

Basic Python knowledge (loops, functions, libraries like NumPy). No prior ML or statistics background needed—this course builds from the ground up.

Why this matters for Indian learners

Machine learning skills are in high demand across Indian tech hubs—from Bangalore startups to FAANG offices in Pune and Hyderabad. Companies like Flipkart, Swiggy, and Microsoft India actively hire ML engineers, and salary expectations for ML-competent developers are significantly higher than general software engineers. Learning in Hindi removes a language barrier that often discourages talented Indian programmers from entering the field, letting you compete faster and with more confidence.

Frequently asked questions

Is this course really free?

Yes. It's a free YouTube playlist. No hidden paywalls, no "premium" version you need to unlock.

How long will it take to complete?

The full course is about 35 hours. If you dedicate 5–7 hours per week and code along (don't just watch), you'll finish in 5–7 weeks. Learning sticks better when you type the code yourself, so pace yourself accordingly.

Will I get a certificate?

No formal certificate from this course. But you will have real projects in your portfolio—code on GitHub, models you've trained—which matter far more to employers than a certificate.