CF

Building APIs with FastAPI

1h 35m 40s
English
Paid
Updated September 2026

Building APIs with FastAPI is a 21-lesson 1 hour 35 minutes self-paced course by Andreas Kretz. APIs sit at the center of most modern data platforms, and Andreas Kretz built this course to teach FastAPI — a fast, modern Python framework for building them — from first principles through deployment.

Course facts

Lessons
21
Duration
1 hour 35 minutes
Level
All levels
Language
English
Updated
2026-09-11
Instructor
Andreas Kretz
Price
Premium

APIs sit at the center of most modern data platforms, and Andreas Kretz built this course to teach FastAPI — a fast, modern Python framework for building them — from first principles through deployment.

API fundamentals

You'll cover what an API actually does in a client-server relationship, the four principles of REST architecture, HTTP methods like GET and POST, response codes, and how API parameters work.

Building and designing your API

After setting up a dev environment with WSL2, Python, VS Code, and FastAPI, you'll prepare a real dataset, then design resources, methods, and schemas around it using OpenAPI and Swagger Editor for documentation.

From code to deployment

Across 21 lessons and a companion GitHub repo, you'll build working endpoints like POST customer, GET customer, and GET invoice, then package the application in Docker and test it with Postman — ending with a deployed, tested API rather than just endpoint theory.

Additional

https://github.com/team-data-science/apis-with-fastapi

Who teaches Building APIs with FastAPI? Andreas Kretz

Andreas Kretz thumbnail

Andreas Kretz is a German data engineer and one of the most widely followed independent voices on data engineering as a career discipline. He runs the Plumbers of Data Science brand and has been publishing tutorial material continuously since the field consolidated around the modern lake-house stack (Spark, Kafka, Snowflake, Databricks, Airflow).

His CourseFlix listing is the largest single-author catalog under this source — over thirty courses spanning data-pipeline construction, streaming architectures, the cloud-native data stack on AWS / Azure / GCP, the Python and Scala tooling that dominates the field, and the soft-skills / career side of breaking into data engineering. Material is paid and aimed at engineers transitioning into data work or already-working data engineers picking up specific tools.

What lessons are included in Building APIs with FastAPI?

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#1: Introduction
All Course Lessons (21)
#Lesson TitleDurationAccess
1
Introduction Demo
02:18
2
What are APIs and what are they used for
08:30
3
Hosting vs using APIs
04:09
4
Methods and Media Types
06:57
5
HTTP response code
05:23
6
API Parameters
04:19
7
Setup environment with WSL2, VS Code & FastAPI
04:56
8
Testing FastAPI
03:22
9
The dataset we use
02:42
10
API Design
04:27
11
Schema implementation preview
05:04
12
OpenAPI & Swagger
05:15
13
POST Customer API
06:24
14
Get Customer API
03:06
15
POST Create Customer Invoice API
06:51
16
GET Invoice API
02:04
17
GET All Invoices for Customer API
03:11
18
Setup Docker and Deploy on WSL2
06:02
19
Testing the APIs with Postman
04:23
20
Security
03:49
21
Conclusion
02:28
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What courses are similar to Building APIs with FastAPI?

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Frequently asked questions

What are the prerequisites for enrolling in this course?
This course assumes a basic understanding of Python, as FastAPI is a Python framework. Familiarity with HTTP methods and REST architecture is beneficial, but not required, as these topics are covered in the initial lessons. Setting up your environment will require basic knowledge of tools like Visual Studio Code and WSL2.
What projects or exercises will I work on during the course?
Throughout the course, you will construct an API using a prepared dataset. You will implement various endpoints such as POST and GET for customer and invoice APIs. Additionally, you will deploy your API using Docker and test it with Postman, providing a comprehensive, hands-on development experience.
Who is the target audience for this course?
The course is ideal for developers who want to gain foundational skills in API development using FastAPI. It is particularly suited for those interested in learning how to design, develop, and deploy APIs efficiently and who wish to leverage modern tools like Docker and Postman for testing and deployment.
How does this course compare to other API development courses?
This course focuses specifically on FastAPI, a modern and efficient Python framework. Unlike some general API courses, it includes detailed instruction on setting up development environments, using OpenAPI and Swagger for documentation, and deploying with Docker. The course also emphasizes practical testing with Postman.
What specific tools and platforms will I learn to use?
You will learn to use FastAPI for building APIs, Docker for deployment, and Postman for testing. The course also covers setting up your development environment with WSL2 and Visual Studio Code, and using OpenAPI and Swagger Editor for API documentation.
What topics are not covered in this course?
The course does not cover advanced API topics such as GraphQL, advanced security protocols beyond basic security strategies, or in-depth database integration. It focuses primarily on RESTful APIs using FastAPI and essential tools for deployment and testing.
How much time should I expect to dedicate to this course?
The course consists of 21 lessons. While the exact runtime is not specified, it is recommended to allocate additional time for hands-on exercises and setting up the development environment. The time commitment will vary based on your familiarity with the prerequisites and your pace in completing the exercises.