Deep Learning for Beginners: Core Concepts and PyTorch

About this course

Are you interested in Artificial Intelligence (AI), Machine Learning and Artificial Neural Network?

Are you afraid of getting started with Deep Learning because it sounds too technical?

Have you been watching Deep Learning videos, but still don’t feel like you “get” it?

I’ve been there myself! I don’t have an engineering background. I learned to code on my own. But AI still seemed completely out of reach.

This course was built to save you many months of frustration trying to decipher Deep Learning. After taking this course, you’ll feel ready to tackle more advanced, cutting-edge topics in AI.In this course:

We assume as little prior knowledge as possible. No engineering or computer science background required (except for basic Python knowledge). You don’t know all the math needed for Deep Learning? That’s OK. We'll go through them all together - step by step.

We'll "reinvent" a deep neural network so you'll have an intimate knowledge of the underlying mechanics. This will make you feel more comfortable with Deep Learning and give you an intuitive feel for the subject.

We'll also build a basic neural network from scratch in PyTorch and PyTorch Lightning and train an MNIST model for handwritten digit recognition.

After taking this course:

• You’ll finally feel you have an “intuitive” understanding of Deep Learning and feel confident expanding your knowledge further.

If you go back to the popular courses you had trouble understanding before (like Andrew Ng's courses or Jeremy Howards' Fastai course), you’ll be pleasantly surprised at how much more you can understand.

You'll be able to understand

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.