LLMs Deep Dive
3 chapters · LLM Infra

A field guide toLLM Infrastructure & Scaling

Building and running LLMs at scale — distributed training, inference & serving, and research engineering.

chapters
3chapters
practice questions
197practice questions
coding problems
17coding problems
What's inside

Reading, until it actually sticks

01

AI code review

Submit a solution, get a focused critique — correctness, style, complexity — in seconds.

Submissionsoftmax.py
1def softmax(x):
2 e = np.exp(x - x.max())
3 return e / e.sum()
All 5 tests passed
02

On-demand AI tutor

Stuck on a paragraph? One click and a tutor re-explains it with more intuition, more math, or a fresh angle.

Tutorshort

What is attention?

Attention weighs tokens by relevance.

03

Progress tracking

Chapters read, questions understood, problems solved — quietly tracked as you go.

Chapter 013/4
  • TokenizationRead
  • AttentionRead
  • Positional encodingsRead
  • Layer normNext
The syllabus

Everything, in one parts