Do I need prior experience building SaaS applications?

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.

What technologies does this course use?

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.

Will I have a deployable product by the end of 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.

When will I have access to the lectures and assignments?

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.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Build a Production SaaS Application with AI

This course is part of AI Tooling Specialization

Instructor: Alfredo Deza

Included with

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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.