Hands-On AI: Vibe Coding in Python with Cursor

Hands-On AI: Vibe Coding in Python with Cursor

1h 5mIntermediate2025-09-29

Authors

Maggie Ma

Maggie Ma

Course details

AI coding tools are transforming how we build software—and Cursor is one of the most powerful IDEs built for this new way of working. In this course, geospatial data scientist Maggie Ma shows you how to use Cursor to boost your Python development through a technique called vibe coding: fast, collaborative, AI-assisted programming. Explore real-world use cases like building machine learning models, developing APIs, and scripting automations—all with AI support. Plus, learn best practices for prompting, structuring projects, and choosing the right tools for the job. Whether you’re a data scientist, backend developer, or curious builder, this course will help you work smarter and ship faster with AI.

Learning objectives
Set up and navigate Cursor as your AI-powered coding environment for Python development.
Use AI features in Cursor to write, refactor, debug, and document Python code efficiently.
Apply best practices for prompting and planning to collaborate effectively with AI in your coding workflow.
Compare Cursor with other AI coding tools and choose the right tool for your specific project or role.
Complete a real-world coding project using Cursor, applying vibe coding techniques from idea to execution.

Skills covered

CursorAnysphereAI Builders and Low/No-Code ToolsAI Development Tools and PlatformsProgramming FoundationsBuilding with AIPythonProgramming LanguagesOpen SourceSoftware DevelopmentOne-Off

Concepts

Introduction

  • Benefits of AI-powered Python development
  • Navigating the Cursor interface

Introduction to Vibe Coding

  • Building a recipe app
  • Project walk-through

Vibe Coding Best Practices

  • Vibe coding approaches
  • Comparing AI code editors - Replit, v0, Cursor, Windsurf
  • Planning projects with AI

Cursor Power Tools

  • Generating code with AI
  • Intermediate prompt writing
  • Debugging
  • Refactoring code
  • Auto-documentation

Conclusion

  • Key takeaways and next steps
40,000 Toman