Deep Learning Tutorials (CodeBasics)

About this course

Deep learning has transformed everything from image recognition to natural language processing—and this CodeBasics playlist breaks it down into digestible pieces. You'll move from neural network fundamentals through CNNs, RNNs, and GANs, all using TensorFlow. CodeBasics brings real clarity to concepts that often feel abstract, making this an ideal bridge between basic machine learning and production-level deep learning work.

What you'll learn

• Build and train feedforward neural networks from scratch using TensorFlow
• Understand convolutional neural networks (CNNs) and apply them to image classification tasks
• Work with recurrent neural networks (RNNs) for sequence data and time-series problems
• Implement generative adversarial networks (GANs) and understand their architecture
• Optimize model performance through backpropagation, loss functions, and hyperparameter tuning
• Debug common deep learning pitfalls: overfitting, vanishing gradients, and training instability
• Deploy models and understand when to use each architecture for real-world problems

Who this is for

You're ready for this if you've got Python basics and understand machine learning fundamentals. This course works best for people who want to move beyond shallow learning techniques into the deep learning tools that power modern AI applications.

• ML engineers building career depth — master the architectures you'll encounter in production systems and job interviews
• Data scientists expanding skill scope — add deep learning to your toolkit for computer vision and sequential data problems

Prerequisites

Solid Python programming skills and familiarity with basic machine learning concepts (training/test splits, overfitting, gradient descent). Linear algebra basics help but aren't essential—CodeBasics explains what you need as you go.

Why this matters for Indian learners

Deep learning roles in India are among the highest-paying AI positions, with companies like TCS, Infosys, Flipkart, and startups like Instadeep actively hiring. Whether you're aiming for roles in computer vision (autonomous systems, medical imaging), NLP (text analytics, chatbots), or generative AI, deep learning is now table stakes. This free course gives you the foundation without the ₹50,000–₹2,00,000 price tag of premium bootcamps.

Frequently asked questions

Is this course really free?

Yes, completely free. CodeBasics publishes on YouTube with no paywalls or hidden costs.

How long will it take to complete?

The playlist is around 30 hours of video. At a comfortable pace of 5–6 hours per week, you're looking at 5–6 weeks. Don't rush—deep learning clicks better when you pause and tinker with code.

Will I get a certificate?

No official certificate is offered, but the real credential is what you can build and explain in interviews. Many learners create a GitHub portfolio with projects based on what they learn here.