[ralusek]

Sorry for failing to clarify:

> Three years ago we pioneered Deep Learning from the Foundations, an in depth course that started right from the foundations—implementing and GPU-optimising matrix multiplications and initialisations

They're talking about how Part 1 starts

[idf00]

Deep Learning from the Foundations IS part 2. They are not talking about how part 1 starts. They are talking about how part 2 starts. This mirrors how their book is written, with the content typically in Deep Learning for Foundations being the second half of the book. I've taken the courses every year, it's always been like that.

You should consider taking a look at part 1 of the course if you want to understand the starting curriculum: https://course.fast.ai/

[Yenrabbit]

'Deep learning from the Foundations' was the previous version of this new course, but both built on their respective part 1s. So part 1 is 'practical deep learning for coders', very good intro to DL for getting things done that starts with big wins using pretrained models and then digs into them enough that you know how to make them better. Part 2 is for those wanting to go all the way to implementing the ideas 'from scratch', reading papers and diving into advanced topics.