What you'll learn:
Develop an intuitive understanding of Deep Learning
Visual and intuitive understanding of core math concepts behind Deep Learning
Detailed view of how exactly deep neural networks work beneath the hood
Computational graphs (which libraries like PyTorch and Tensorflow are built on)
Build neural networks from scratch using PyTorch and PyTorch Lightening
You'll be ready to explore the cutting edge of AI and more advanced neural networks like CNNs and Transformers
You'll be able to understand what deep learning experts are talking about in articles and interviews
You'll be able to start experimenting with your own AI projects using PyTorch

Requirements
Basic Python programming knowledge
Highschool math

Description
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 what experts like Geoffrey Hinton are saying in articles or Andrej Karpathy is saying during Tesla Autonomy Day.

You'll be well equipped to start exploring more advanced neural network architectures like CNNs, RNNs, transformers, etc and start your journey towards the cutting edge of AI.

You can start experimenting with your own AI projects using PyTorch

Who this course is for
Students who want learn Deep Learning for the first time
Beginners who want to finally understand Deep Learning at an intuitive level

Citación :

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