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Pydantic for Structured Data Validation in LLM Workflows

Master the art of building reliable, production-ready LLM applications with Pydantic for structured data validation. This hands-on course teaches you how to move beyond free-form AI text outputs and implement robust validation schemas that ensure every response from large language models is accurate, complete, and ready for downstream processing. Learn to design structured output schemas, parse and validate JSON responses from LLMs, and handle validation errors gracefully — skills essential for anyone building AI-powered systems that need to perform consistently at scale.

Dive deep into advanced validation patterns including nested models, enums, unions, and custom validators that give you fine-grained control over LLM outputs. Explore real-world applications such as building a customer support assistant that extracts ticket details, validates customer data, and routes requests using structured output. You will also learn to integrate Pydantic with modern LLM APIs, agent frameworks, function calling, tool calling, and backend services like FastAPI — equipping you with the expertise to design multi-step LLM pipelines where every stage is structured, validated, and production-ready.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Course Code: M670

Fee

₹5,000,000.00

Course Date

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Post-Course Support

We provide free consultation related to the subject matter after the course. Please email your queries to info@tertiarycourses.com.ng and we will forward your queries to the subject matter experts and get back to you asap.

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Course Details

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

Course Info

Prerequisite:

Basic knowledge of Python is assumed

HRDF Funding

Please refer to this video https://youtu.be/Kzpd-V1F9Xs

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How to submit grant applications for HRD Corp Claimable Courses

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Second, Click Application

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The application status will be updated via the employer’s dashboard, email, and the e-TRiS inbox.

Job Roles

  • AI Engineer
  • Machine Learning Engineer
  • NLP Engineer
  • LLM Fine-Tuning Specialist
  • AI Research Scientist
  • Data Scientist
  • Deep Learning Engineer
  • AI Solutions Architect
  • MLOps Engineer
  • AI Product Manager
  • Conversational AI Developer
  • AI Infrastructure Engineer
  • Natural Language Processing Researcher
  • AI Consultant
  • Machine Learning Operations Specialist
  • AI Application Developer
  • Data Engineer
  • AI Technical Lead
  • Prompt Engineer
  • AI Systems Integration Specialist

Trainers

Dr. Nouar AlDahoul: Dr. Nouar AlDahoul is an AI researcher and developer with a PHD degree from IIUM Malaysia. She has +7 years of hands-on experience in machine learning including deep and reinforcement learning. She has been working as a researcher in many research centers such as UM, IIUM, MMU universities. She has published many papers in different journals and conferences. She has conducted more than 30 classes in Tertiary Malaysia Courses. Her research interests are: Deep learning, Reinforcement learning, computer vision, NLP, Data visualization and analysis, and IOT.

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