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.
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您将学到什么
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
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April 2026
作业
3 项作业
授课语言:英语(English)
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