Ask HN: "Best" LLMs and foundation models education materials recommendations?
Dear all,<p>Today on HN I saw a post mentioning [Gen AI Handbook](https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=40604093), in which a comment mentioned the [MIT Deep Learning course](http:&#x2F;&#x2F;introtodeeplearning.com&#x2F;). It seems that they cover some LLMs &#x2F; foundation models, but not all.<p>So I googled a bit and found out that Stanford ([NLP with DL](https:&#x2F;&#x2F;web.stanford.edu&#x2F;class&#x2F;cs224n&#x2F;)) and Princeton ([Understanding LLMs](https:&#x2F;&#x2F;www.cs.princeton.edu&#x2F;courses&#x2F;archive&#x2F;fall22&#x2F;cos597G&#x2F;)) both offer great courses on these topics.<p>I was wondering that for people who have more experience with DL and&#x2F;or LLMs, if I want to focus more on LLMs &#x2F; foundation models (somewhat motivated by [this YC podcast episode](https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=fmI_OciHV_8)), <i>which of the above materials and&#x2F;or other contents you would recommend, if I already have [the Transformer book](https:&#x2F;&#x2F;transformersbook.com&#x2F;)?</i><p>Some context: I am a math graduate student with a 13-year-old Macbook Pro; I recently purchased a Mini PC Beelink SER5 and had some fun with small llamafiles...<p>Many thanks!