Video course · 8 chapters · 82 min · certificate
Pydantic Crash Course: Data Validation for Python & AI Apps
A complete Pydantic crash course: type hints, your first model, validation and fields, nested models, Pydantic Settings for configuration, and structured output from LLMs, building up in complexity with practical examples.
What you'll learn
- Use Python type hints confidently
- Create Pydantic models
- Validate data with fields and validators
- Compose nested models
- Manage configuration with Pydantic Settings
- Get structured output from LLMs
Chapters
8 chapters · 82:22-
10:38
01Intro Members
Introduction to Pydantic
What Pydantic is and why it matters for Python and AI apps.
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9:24
02Basics Members
Type hints
How Python type hints work.
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9:13
03Models Members
Your first model
Creating a BaseModel class like a User.
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33:30
04Validation Members
Validation and fields
Field constraints, validators and error handling.
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1:12
05Models Members
Nested models
Models inside models.
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6:20
06Config Members
Pydantic Settings
Loading configuration and environment variables with validation.
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10:01
07AI Members
Structured output with LLMs
Turning LLM text into structured data with Pydantic models.
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2:04
08Recap Members
Summary and next steps
Recap of best practices.
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