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Hands-On with Cursor AI

Executive Summary

This 2-day, live course empowers developers to leverage Cursor—the next-generation AI coding platform. Participants will master key features, advanced integration, and intelligent workflows that set Cursor apart from other tools. Through hands-on training, teams will boost development speed, improve code quality, and collaborate effectively while maintaining privacy and code ownership.

Productive tech team collaborating

Course Details

This live, instructor-led course is designed to upskill software teams in using Cursor AI, a next-generation AI coding platform. Through interactive labs and hands-on exercises, participants will build real projects while enhancing team velocity, improving code quality, and strengthening collaboration—without compromising privacy, security, or code ownership.

Objectives:

  • Differentiate Cursor editor from other AI coding tools in terms of features, privacy, and licensing.
  • Treat AI as a code translator that bridges human intent to executable code.
  • Migrate from Copilot and configure Cursor within VSCode or JetBrains environments.
  • Leverage custom modes, inline suggestions, and workflow orchestration for real productivity.
  • Implement persistent context rules and structure large-scale projects efficiently.
  • Build and debug Model Context Protocols (MCP) for scalable intelligent development.
  • Customize AI models (local or remote) based on performance, privacy, or project goals.
  • Apply prompt engineering best practices for authoring, testing, and reviewing AI-generated code.
  • Conduct contextual, AI-assisted code reviews aligned with industry and security standards.
  • Complete a full development cycle using Cursor—from user story to sprint planning.

Duration

14 hours of live instruction delivered across 2 to 4 days. designed to minimize work disruption. Includes recordings, full environment setup, and optional local development instructions.

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Course Outline

This live, instructor-led course is designed to upskill software teams in using Cursor AI, a next-generation AI coding platform. Through interactive labs and hands-on exercises, participants will build real projects while enhancing team velocity, improving code quality, and strengthening collaboration—without compromising privacy, security, or code ownership.

Orientation and Setup
  • Developers seeking to optimize GitHub Copilot usage within VSCode, CLI, and Copilot Chat.
  • Key differences from Copilot and other AI programming tools (e.g., GitHub Copilot vs. Cursor).
  • Cursor AI pricing, privacy, and ownership.
  • Documentation and support.
  • Environment setup (VSCode, JetBrains, local/cloud).
  • Commands, shortcuts, and settings.
Prompting and Interaction Models
  • Translating intent → output: mental models.
  • From human thought → prompt → code.
  • AI as a collaborative partner, not just an autocompleter.
Core Features of Cursor
  • Integrated editing and AI code suggestions.
  • Codebase awareness and context handling.
  • Real-time collaboration capabilities.
Managing Context
  • Indexing projects and managing .cursorignore.
  • Persistent project and user rules.
  • Rule syntax (plain text, MDC format).
  • Best practices for context management.
  • Using the @> symbol to guide context.
  • Integrating external code sources.

Model Context Protocol (MCP)
  • Architecture: servers, clients, data sources.
  • Cursor’s MCP SDKs: Python, TypeScript, Java, Kotlin, C#.
  • Integrating third-party APIs.
  • Debugging and configuration in Cursor.
AI Models in Cursor
  • Model types: premium, agentic, local (Ollama).
  • Model selection and switching.
  • Hosting options and privacy modes.
  • Connecting to public APIs or custom models.
Custom Modes in Depth
  • Anatomy of a custom mode.
  • Assigning models, tools, keybindings.
  • Advanced configuration and use cases.
AI Prompt Engineering
  • Core principles: specificity, clarity, context, iteration.
  • Structuring effective prompts.
  • Use of boilerplate, comments, and prompt chains.
  • Task-based model and mode selection.
AI-Powered Code Reviews
  • AI code review strategies.
  • Asking Cursor for reviews.
  • Reviewing for correctness, performance, security.
  • Industry best practices and anti-pattern detection.
End-to-End Project Build
  • Plan user stories and generate repo structure.
  • Build out CRUD ops with prompts.
  • Insert inline snippets, write tests.
  • Fix lint errors, refactor code.
  • Apply design patterns, generate documentation.
  • Sprint planning with Cursor.

Prerequisites

  • This AI Cursor course is ideal for professional software engineers—regardless of language—who are comfortable with basic Git and IDE workflows.
  • Prior exposure to GitHub Copilot or similar AI code tools is a plus. It is also suited for:
    • Developers seeking to optimize GitHub Copilot usage within VSCode, CLI, and Copilot Chat.Engineering teams evaluating GitHub Copilot Enterprise for organizational deployment.
    • Technical leads and dev managers aiming to enhance productivity with AI tools.This course delivers immediately actionable skills.

Training Materials

All students receive a complete set of course materials and downloadable recordings of every session. You'll work in a fully configured, cloud-based environment for each class, and if you'd rather develop locally, you'll have clear, step-by-step setup instructions for both in-class exercises and ongoing practice. Please note that to keep our live sessions focused on the curriculum, we won't be offering real-time troubleshooting for local setups—but our detailed guides and post-class support resources will ensure you're up and running smoothly.