Pydantic for Structured Data Validation in LLM Workflows

Topic 1: Foundations of Structured Output & Pydantic Basics

• Why free-form LLM text is not enough for production systems
• What structured output is and why it matters in LLM workflows
• Common failure modes in unstructured LLM responses
• Introduction to Pydantic
• Parsing and validating JSON responses from LLMs
• Handling validation errors gracefully

Topic 2: Using Pydantic with LLM APIs & Agent Frameworks

• Designing structured schemas for LLM outputs
• Prompting LLMs for structured responses
• Using Pydantic models directly in API calls
• Structured outputs with modern LLM providers
• Function calling and tool calling with Pydantic models
• Ensuring completeness and correctness before triggering downstream systems
• Example: Customer Support Assistant
• Extracting ticket details
• Validating customer data
• Routing requests based on structured output

Topic 3: Advanced Validation Patterns & Production Workflows

• Nested models and complex schemas
• Enums, unions, and custom validators
• Combining structured outputs and tool-calling in agent workflows
• Using Pydantic in multi-step LLM pipelines
• Defensive programming: validating at every stage
• Integrating Pydantic into FastAPI or backend services
• How popular frameworks use Pydantic under the hood
• Designing robust LLM systems where every step is structured and validated

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Minimum Entry Requirement

Knowledge and Skills

• Able to operate using computer functions
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

• Positive Learning Attitude
• Enthusiastic Learner

Experience

• Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

TBD

Hardware: Window or Mac Laptops

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Quah Chee Yong: Quah Chee Yong is a ACTA trainer. Chee Yong is an experienced professional who has held various Technical, Operations and Commercial positions across several industries A firm believer that AI can create a better world, he has equipped himself with the Knowledge and Skills in the fields of Data Science, Machine Learning, Deep Learning and Cloud Deployment He has a deep passion for training & facilitating and is currently a Singapore WSQ certified Adult Educator. He particularly enjoys the interactive engagements with his fellow trainers and learners.

Solomon Soh Zhe Hong: Solomon is ACTA certified and has trained and coached over 100 professionals in the area of data science, python programming and coding. Solomon is a Certified AI Engineer Associate by AI Singapore and holds certifications in Alibaba Cloud Architect and Alteryx respectively. Solomon interests include Reinforcement Learning, Natural Language Processing and Time-Series analysis.

Marcel Leng: Marcel Leng is a ACTA certified. Marcel graduated with majors in Applied Mathematics and Physics from the National University of Singapore.

His core specialisation skills are R, Python, Machine Learning, Statistical Analysis, and Data Visualisation in Tableau. His current interests include Machine Learning, Deep Learning, Artificial Intelligence, Internet of Things, Robotics and Programming.