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AI Engineering track

LLM Fundamentals

How LLMs work, autoregression, context windows, temperature and sampling.

6 concepts3 labs
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Concepts

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Work through the concepts in order, or jump to what you need.

1

What Language Models Are

Concept · Hands-on lab included

2

Autoregressive Generation

Concept · Hands-on lab included

3

Context Windows & Limits

Concept · Hands-on lab included

4

Temperature & Sampling

Concept · Hands-on lab included

5

System vs User Prompts

Concept · Hands-on lab included

6

Calling LLM APIs

Concept · Hands-on lab included

Practice

Hands-on labs

Apply what you've learned in guided, production-style environments.

Browse all labs

Predict the Next Token, Statistically

25 min · beginner · What Language Models Are

Temperature Shapes the Sampling Distribution

25 min · intermediate · Temperature & Sampling

First Chat Call with Metadata

30 min · beginner · Calling LLM APIs

Continue

Next modules

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The Python skills AI engineering builds on — typing, async, packaging and testing.

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HTTP, REST, auth, rate limits, SDK patterns and API design for AI systems.

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Data Handling

Preparing documents, JSON, embeddings pipelines and data validation for AI.

DevOpsForge - AI Engineering · LLM Fundamentals
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