LEARNING SERIES · Intermediate
Building Python Applications with AI Assistance
An end-to-end path for turning an idea into an agent-built Python application that is refined, security-reviewed, acceptance-tested and documented.
Start learning ↓LEARNING PATH
Complete the modules in order.
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01
Guide · 8 MIN READ
Module 1: Develop a Valuable Application Idea
Turn a real problem into a Python application proposal with clear users, value, MVP scope and success measures.
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02
Guide · 10 MIN READ
Module 2: Prepare the Application Specification
Translate the idea into a buildable and testable specification covering requirements, data models, user flows and acceptance criteria.
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03
Guide · 11 MIN READ
Module 3: Direct a Vibe Coding Agent to Build the Application
Provide clear specifications, constraints and a definition of done so a coding agent builds the application in a controlled, reviewable way.
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04
Guide · 9 MIN READ
Module 4: Improve UI/UX without Breaking Functionality
Audit and improve user experience, responsive design, accessibility and interface states incrementally.
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05
Guide · 11 MIN READ
Module 5: Conduct an Application Security Review
Use an agent as an audit assistant to identify evidence-backed risks, implement fixes and add security regression tests.
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06
Guide · 10 MIN READ
Module 6: Run Functional Acceptance Testing (FAT)
Turn requirements and acceptance criteria into a FAT plan with test data, evidence, defect management and exit conditions.
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07
Guide · 10 MIN READ
Module 7: Document the Current State of the Application
Produce an application-state document that lets others run, review, maintain and continue development safely.
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08
Guide · 14 MIN READ
Module 8: Push to GitHub and Deploy the Application
A guide to pushing a Python application to GitHub and deploying to Render Free, Railway Free or another provider with migrations, smoke tests and persistence checks.
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09
Guide · 10 MIN READ
Module 9: Python Application Final Project
A final project and 100-point rubric demonstrating that a Python application was properly built, tested, secured, documented and deployed.
PERSONAL NOTES
Capture what you want to apply.
KNOWLEDGE CHECK
Check your understanding.
Choose one answer for each question. You can retry at any time.
FINAL OUTCOME
Complete your final project.
Final outcome: a runnable, deployed Python MVP with a specification, GitHub repository, reviewed UI/UX, automated tests, security risk register, FAT report, State of the Application and final project assessment.
Start final task ↗