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Build a Production SaaS Application with AI

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Build a Production SaaS Application with AI

This course is part of AI Tooling Specialization

Instructor: Alfredo Deza

Included with

Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Apply MVP planning and API design patterns to build a documented, tested application from initial project structure through automated verification
Evaluate containerization strategies, automating container builds with CI pipelines, and publishing production images to a container registry
Analyze and design conversion-focused landing pages, implement API key authentication for monetization, and deploy sites with developer docs

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

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Build your subject-matter expertise

This course is part of the AI Tooling Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

Learn to build and launch a complete Software as a Service (SaaS) application using AI-assisted development techniques. This course walks through the entire product lifecycle, from planning a Minimum Viable Product (MVP) to deploying a monetized Application Programming Interface (API) service. You will build a Python API using FastAPI, define data models, create documented endpoints, and verify behavior with an automated pytest test harness. The course covers Docker containerization from Dockerfile creation through container testing, automated builds via Continuous Integration (CI) pipelines, and publishing images to a container registry for production distribution. In the second module, you will build the go-to-market foundation: designing conversion-focused landing pages, structuring pricing tiers, deploying a marketing site to GitHub Pages, implementing API key authentication for metered access, and writing developer documentation that drives adoption. Throughout the course, Large Language Model (LLM) tools accelerate development from architecture planning through code generation. By completing this course, you will have the skills to take an AI-powered SaaS product from concept to production launch.

What's included

19 videos5 readings1 assignment

19 videosTotal 80 minutes

Introduction0 minutes
What Are We Building4 minutes
Architectural Overview5 minutes
Planning an MVP5 minutes
Leveraging LLMs for Development5 minutes
Conclusion1 minute
Introduction0 minutes
Initial Project Structure5 minutes
Exploring Data and Defining Endpoints10 minutes
Defining the API with Documentation6 minutes
Verifying the API4 minutes
Creating a Test Harness5 minutes
Conclusion1 minute
Introduction1 minute
Containerizing the Application6 minutes
Testing and Verifying the Container8 minutes
Automating Containerization7 minutes
Publishing the Container to a Registry6 minutes
Conclusion1 minute

5 readingsTotal 5 minutes

Key Terms1 minute
Reflection1 minute
Key Terms1 minute
Reflection1 minute
Key Terms1 minute

1 assignmentTotal 30 minutes

Foundations of an API30 minutes

What's included

9 videos4 readings1 assignment

9 videosTotal 39 minutes

Introduction1 minute
Create a Converting Landing Page4 minutes
Refine the Pricing Page3 minutes
Design an About Us Page7 minutes
Deploy Your New Site to GitHub Pages4 minutes
Conclusion2 minutes
Implementing API Key Access7 minutes
Adding Developer Documentation5 minutes
Overview and Next Steps6 minutes

4 readingsTotal 40 minutes

Key Terms10 minutes
Reflection10 minutes
Key Terms10 minutes
Reflection10 minutes

1 assignmentTotal 30 minutes

Marketing and monetization30 minutes

What's included

1 video1 reading1 assignment

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Alfredo Deza

Pragmatic AI Labs

33 Courses1,605 learners

Offered by

Pragmatic AI Labs

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Frequently asked questions

No prior SaaS experience is required. The course builds the application from scratch, starting with MVP planning and progressing through API development, containerization, and marketing site deployment. Basic Python proficiency and familiarity with the command line are sufficient.

The course uses Python with FastAPI for API development, pytest for automated testing, Docker for containerization, GitHub Pages for static site hosting, and Hypertext Transfer Protocol (HTTP) API key authentication for access control. LLM tools assist with code generation and architectural planning throughout the course.

Yes. The course produces a containerized API service published to a container registry, a marketing website with landing and pricing pages deployed on GitHub Pages, API key authentication for metered access, and developer documentation. The capstone project integrates all components into a production-ready SaaS application.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.