Neural Networks: Zero to Hero

About this course

Neural Networks: Zero to Hero is Andrej Karpathy's definitive YouTube series that teaches you to build neural networks and GPT models from the ground up—line by line, in PyTorch. Karpathy, a leading AI researcher and educator, distills years of deep learning expertise into a hands-on curriculum that demystifies the math and code behind modern AI. This course is ideal if you want to move beyond tutorials and truly understand how the systems reshaping technology actually work.

What you'll learn

• Build neural networks from scratch using NumPy and PyTorch, implementing backpropagation and gradient descent by hand
• Understand the architecture and mathematics behind transformers, attention mechanisms, and how GPT models generate text
• Train a character-level language model and scale it to generate coherent sequences
• Debug and visualize neural network behavior using techniques like activation analysis and loss curve inspection
• Optimize training workflows with batch processing, learning rate scheduling, and regularization strategies
• Implement tokenization and embedding layers that convert raw text into neural network inputs
• Gain intuition for why deep learning works—moving past formulas to genuine conceptual understanding

Who this is for

You're an ideal fit if you've written Python code before, understand basic calculus and linear algebra, and are ready to invest time in building mental models—not just running pre-trained models. Whether you're pivoting into AI, strengthening fundamentals for a role in tech, or feeding genuine curiosity about how AI works, this course meets you where you are.

• AI/ML enthusiasts — move from theory blogs to hands-on competency by coding real neural networks and training them end-to-end
• Software engineers — deepen your understanding of AI systems you'll integrate or maintain, and gain confidence to experiment beyond frameworks
• Career-switchers into AI — build a credible foundation and portfolio piece that shows interviewers you can think, not just copy-paste

Prerequisites

Solid Python programming skills and comfort with high school–level math (derivatives, matrix multiplication). You don't need prior machine learning experience, but you should be willing to work through mathematical notation and multi-hour coding sessions. A GPU (NVIDIA, for faster training) is helpful but not required.

Why this matters for Indian learners

India's AI hiring market is expanding rapidly, with roles at startups like Unacademy, Swiggy, Flipkart, and enterprise giants like TCS and Infosys offering premium salaries for engineers who understand deep learning fundamentals—not just API users. Machine learning engineers in India's tech hubs command 15–30 LPA starting salaries, with growth into 40+ LPA for those who can architect and train models. This course gives you the rare, defensible expertise that distinguishes you in a crowd of online-course résumés and makes you genuinely valuable to teams building AI products.

Frequently asked questions

Is this course really free?

Yes, completely free. All videos are on Andrej Karpathy's YouTube channel with no paywalls, logins, or hidden costs.

How long will it take to complete?

The video content is 25 hours, but expect 50–75 total hours once you code along, experiment, and revisit concepts. A realistic pace is 5–8 hours per week, so plan for 3–5 months if you're balancing this alongside work or study.

Will I get a certificate?

No formal certificate, but you'll have a portfolio of working code and trained models—often more valuable to employers and your own learning than a branded credential.