Learning Pydantic: Advanced Data Validation In Python (Udemy.com)
The Complete Guide To Pydantic Including A Full Capstone Project with FastAPI And Redis
Created by: Andy Bek
Last updated July 2026
What you will learn
- Gain an in-depth understanding of what Pydantic is and how it is used
- Practice defining Pydantic data models using modern type hints, custom validations, and fine-tuned configuration
- Learn how to define complex, interdependent, and nested data models with Pydantic
- Serialize model instances into JSON and deserialize incoming data
- Practice using Pydantic in the context of building and deploying a real-world python web API
- Master relevant concepts in modern python application development, like dependency management and version control
How it compares
Against the other 518 rated Udemy courses in Software Development on CourseDuck:
- Rating4.5 out of 5higher than 41% of them
- Reviews163#369 of 519 by number of reviews
- Length11.3 hourslonger than 73% of them
- Last updatedJuly 2026more recently than 81% of them
Course Description
Welcome to the best resource online for learning modern Pydantic, a data validation library that has taken the python community by storm.
Pydantic is was first released in 2018 and has since become one of the most popular python libraries. It is nowadays downloaded more than 130 million times a month, and is used by some of the largest organizations out there, from the tech giants like Google, Amazon, Apple, Meta, and Netflix, to large conglomerates in various other industries, such as Starbucks, JPMorgan Chase. Oh, and yes, even NASA.
There's a good reason for this. Pydantic is a powerful library that elegantly solves a very common problem in software development: data validation.
Pydantic's speed, simple declarative syntax, and extensibility make it an indispensable utility in modern python development.
And in this course, you will learn everything you need to know to get started with Pydantic, from the very basics of defining data models, to more advanced topics such as fields with factory defaults, creating custom model-validators, data serialization, and much more.
The first part of the course will be purely about pydantic, where we explore it in isolation. You will learn:
how to define data models with pydantic
how to compose more complex models from simpler ones via inheritance
the foundations of type hinting in python, including enumerations, literals, and other advanced types-
how to use pydantic's powerful validation system
how to serialize and deserialize data
how to extract models to schemas
how to validate data against pydantic models
Then in the second part of the course we will turn our attention to the Capstone Project, where we will use pydantic to develop and deploy a python web API that allows users to create and vote on polls. This app will use Redis as our durable key-value data store, and will be deployed to production as a serverless function.
The Capstone will be developed step by step, in a series of about 30 skill challenges, where you will be asked to incrementally implement small features. This will give you the opportunity to practice what you've learned in the first part of the course, and to:
get a practical feel for how Pydantic is used in real-world applications
learn about modern API development with python
understand what Redis is and how it can be used as a durable data store
learn about virtual environments and dependency management in python
practice using git and github
learn the basics of serverless computing by deploying the API as a serverless function
The course will use the latest version of Pydantic, which leverages the power of Rust to achieve blazing fast performance.
Also, if you're new to python or haven't used the used the language in a while, there's a full-featured python crash course included as an extra appendix which will get you up to speed in no time.
I'm very excited to share this with you, and I look forward to seeing you in the course!
Instructor Details
- 4.5 Rating
163 Reviews
Andy Bek
Hi! I'm Andy, a freelance software developer and capital markets consultant based in Toronto, Ontario. I've spent close to a decade working with data, using code to automate business workflows, and consulting financial institutions on data-intensive applications.
Although I'm comfortable in a number of programming languages, nothing beats python on a ROIE (return on invested effort) basis. It is my go-to language and also my focus here on Udemy.
Aside from teaching, I specialize in consulting financial institutions in post-trade services technology.
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Reviews
By Susan Abraham on 8/20/2026
Good explanation
By Ritesh Bansal on 1/11/2026
Yes the course is very good. The capstone project takes all the learning to a new level. Thanks. Speed and contents is just great. Thanks
By Muhammad Hassan on 11/8/2025
this is best course for pydantic but its overlloaded with the fastapi and python course. Instructor explain very well but overloaded the course .
By Fernando Hernández on 7/12/2025
It is the second course I take from Andy, and honestly it is as always one of the best courses related to python, in this specific case to Pydantic, you really learn from the basics to things you didn't know you can do, it is totally worth the course, plus you learn some tips, directly unrelated to Pydantic.
By Yaron Klein on 6/28/2025
Covers using Pydantic and FastApi from the initial installs all the way to deployment on the web using Github and Vercel. Now in the age of CoPilots and Vibe coding do we really need to understand what goes on under the hood ? Well - they'll remember the syntax for us - but if you don't tell them what to do they'll choose some default off the web. The first thing every course on the wonderful new world opening to us says is - "be specific". In the end to "be specific' - you need to understand whats going on under the hood.
By Andrea Dalseno on 6/22/2025
The course is nice, but I think it might have gone deeper in exploring Pydantic features. It's more a (well-done) general overview than a complete guide. About 2/3 of the course is devoted to the capstone project, which is useful but doesn't add much to the first part.
By Rony GHEBALI on 6/18/2025
clear, hands on and simple. Clear english. Awsome complete project with detailed steps including pydantic models, FastAPI handling and data saving modules. Really valuable.
By Kishor Joseph on 1/15/2025
It seems the instructor is really an experienced and seasoned python developer and thus providing value for our money and time. Thank you!
By Tiffani Frost on 5/12/2024
so far so good! i like the pace at which he talks, makes it very easy to listen to at higher speeds which is how i like to consume information :)
By Ferruccio Guicciardi on 1/31/2024
Thanks a lot. I am very enthusiastic about the new empowerment of Pydantic Data Modeling and Data Validation , specially when adding model definitions and constraints. The conversion of documents to JSON, YAML and XML is also very cool. Again, thanks for allowing me to grasp the full power of the Pydantic workflow, the ability of define data models as Python classes, passing data to the model constructor (serialize) and the awesome ability to be able to manipulate the attributes just like any other Python object and optionally , deserialize the data object back out according to business logic and the pycheckers integration.
Quality Score
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Overall Score : 90 / 100









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