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
Part I
