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Course overview

LLMs for Engineers

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1 · Inside the transformer

1Tokens and embeddings
2Attention, step by step
3The transformer block

2 · How models are trained

4Pretraining and scaling laws
5Post-training an assistant
Exercise answers
- Answer: Build a verifiable reward and simulate GRPO advantages

3 · Running models in production

6Sampling and hallucination
7Context windows, KV cache and caching
8Reasoning models and extended thinking
9Choosing and comparing models

CapstoneChoose a model for document extraction Reference implementation

Answers Lesson 5: Post-training an assistant

Step-by-step answer

Core 60 min8 steps

Build a verifiable reward and simulate GRPO advantages

Back to the exercise

Previous answerBase model versus assistant on conveyancing prompts Next answer Measure and catch hallucinations in lease extraction

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