Neural Networks from Scratch in Python

About this course

In this series, Harrison Kinsley from Sentdex walks you through building a neural network completely from scratch using pure Python—no TensorFlow, PyTorch, or other frameworks. You'll see exactly how neurons, layers, and backpropagation work under the hood, transforming abstract math into working code. This is one of the most respected deep-learning foundations courses for anyone serious about understanding what's actually happening inside the models reshaping AI today.

What you'll learn

• Build a functional neural network from scratch using only NumPy and Python
• Understand neurons, activation functions, and how data flows forward through layers
• Implement backpropagation and gradient descent to train your network
• Work with real datasets, preprocess data, and measure model performance
• Debug and troubleshoot training issues by reading the code yourself
• Recognize when and why to use neural networks for different problems
• Develop intuition for hyperparameters like learning rate and batch size

Who this is for

You're a programmer who knows Python and wants to move beyond "plug and play" machine learning. You're curious about how deep learning actually works, and you're willing to spend time on math and code to truly understand it. This course rewards that curiosity.

• Software developers — gain the foundational knowledge to architect AI features in your applications without relying blindly on frameworks
• Data science students and early-career analysts — build credibility and depth before your first machine learning job interview
• AI enthusiasts and career-changers — prove to yourself (and employers) that you understand neural networks deeply, not just superficially

Prerequisites

You should be comfortable writing Python code (loops, functions, arrays). A basic grasp of calculus and linear algebra helps, but the course teaches the relevant math as you go. You don't need prior machine learning or deep learning experience.

Why this matters for Indian learners

India's AI and machine learning job market is exploding—companies like Google, Amazon, and Flipkart are hiring ML engineers, AI researchers, and data scientists at scale. A deep understanding of neural networks sets you apart from candidates who only know high-level libraries. Many Indian tech startups and enterprises building recommendation systems, fraud detection, and NLP products need engineers who can troubleshoot and optimize neural networks, not just call pre-built functions. This course gives you that competitive edge.

Frequently asked questions

Is this course really free?

Yes—completely free. The entire series is hosted on YouTube at no cost. No hidden paywall, no "paid certificate" upsell required.

How long will it take to complete?

The course is about 15 hours of video. If you dedicate 3-4 hours per week, you can finish in 4–5 weeks. Factor in extra time to run the code yourself, experiment, and work through concepts—that's where the real learning happens.

Will I get a certificate?

No formal certificate is offered. However, you'll have a portfolio of working code—a neural network you built yourself—which carries far more weight with employers than any certificate.