CURSOR TRAINING: CODE FASTER WITH AI

We start at the beginning: install Cursor, understand the interface, configure your first AI settings. You'll see how it differs from regular VS Code and why the AI integration changes everything.

You'll create your workspace, set up your preferences, understand the command palette, and configure your API keys for AI features. We'll also cover keyboard shortcuts that'll save you hours.

You'll connect your GitHub account, understand how Cursor handles version control, and set up your first project repository directly in the IDE.

At the end of this module, you have a fully configured Cursor IDE. You know where everything is and you're ready to start coding with AI assistance.

This is where it gets interesting: you'll learn to actually code with AI. We'll see how to write effective prompts, use autocompletion intelligently, and generate functions from natural language.

You'll understand context windows (how much code the AI can see), learn to describe what you want clearly, and use Cursor's chat feature to ask questions about your codebase.

We'll practice generating React components, Python scripts, API endpoints, and database queries just by describing them. You'll see how to accept, reject, or modify AI suggestions.

You'll also learn when to trust the AI and when to double-check, how to handle hallucinations, and how to iteratively improve generated code with follow-up prompts.

At the end of this module, you can write code 5-10x faster than traditional coding. You understand how to collaborate with AI as a coding partner.

Cursor's real power shows up when working across multiple files. You'll learn to edit several files simultaneously, refactor entire features, and maintain consistency across your codebase.

You'll use Cursor's context-aware AI to rename variables across files, restructure folder architectures, and update imports automatically when moving code around.

We'll practice refactoring a messy codebase: extracting reusable components, splitting monolithic files, organizing your project structure, and cleaning up technical debt with AI assistance.

You'll also learn to search across your entire project, use regex for advanced find-and-replace, and leverage Cursor's AI to understand complex codebases you didn't write.

At the end of this module, you can maintain and improve large projects without getting lost. You know how to keep your code clean and organized even as it grows.

Bugs happen. We'll see how to use Cursor to identify issues, understand error messages, and fix problems faster than traditional debugging.

You'll learn to highlight broken code and ask the AI "why doesn't this work?", use Cursor's terminal integration to run tests and see errors, and leverage AI to suggest fixes for common bugs.

We'll practice debugging real scenarios: API calls that fail, UI components that don't render, database queries that return wrong data, and performance issues that slow down your app.

You'll also learn to read stack traces, use console logs effectively, and understand when the issue is in your code vs external dependencies.

At the end of this module, debugging is way less frustrating. You can identify and fix issues in minutes instead of hours.

Real development means version control. You'll master Git workflows inside Cursor: commits, branches, pull requests, and merge conflicts with AI assistance.

You'll learn to write clear commit messages (with AI suggestions), create feature branches, push to GitHub, and handle merge conflicts when they inevitably happen.

We'll practice collaborative workflows: reviewing code changes, understanding diff views, reverting commits when needed, and keeping your Git history clean.

You'll also connect Cursor with GitHub Copilot if you have it, use AI to write better commit messages, and understand best practices for working in teams.

At the end of this module, you're comfortable with Git. You can contribute to team projects without messing up the repository.

Time to put it all together. You'll build 2-3 complete projects from scratch using everything we've learned: a web app, an automation script, or an API.

We'll start with planning (describing the project to AI), generate the initial structure, implement features iteratively, debug issues as they appear, and deploy to production.

You'll practice the full workflow: idea → code → test → deploy. We'll use realistic scenarios like building a task manager app, creating an automated data pipeline with n8n, or developing a REST API with authentication.

You'll also learn to read documentation with AI assistance, integrate third-party libraries, handle environment variables, and optimize performance before shipping.

At the end of this module, you've shipped real projects. You're autonomous with Cursor and ready to build whatever you need without hand-holding.