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Updated 12 months ago

Foundational learning resources

At a glance
The community member who posted the original question is a non-major and front-end developer interested in becoming an LLM (Large Language Model) engineer. The comments suggest that to become an LLM engineer, the community member should focus on studying math, particularly probability, statistics, and linear algebra, as well as learning how to conduct correct and reproducible experiments. The comments also mention a resource, a flipped ML course, that the commenter used when teaching, which they suggest may be helpful for the original poster.
Useful resources
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Bro, I am a non-major and a just front-end developer. I am interested in LLM engineering. What things should I study from the beginning to become an LLM engineer?
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1 comment
vverdverm
Depends on what you are envisioning in terms of an LLM engineer.
  1. Making advancements in algos & systems
  2. Building AI systems that people will use
Certain things will be helpful to both
  • Math, in particular prob/stats & lin alg
  • How to do correct & reproducible experiments
This is one of the resources I used when I taught a flipped ML course when deep vision models were just coming out for the first time. It might seem old or irrelevant, but this is certainly the baseline theory that still underpins today's and tomorrow's techniques.

https://work.caltech.edu/telecourse
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