Cursor AI Essentials
Class Duration
7 hours of live training delivered over 1-2 days to accommodate your scheduling needs
Student Prerequisites
- Basic understanding of programming concepts
- Experience with a programming language such as Java, Python, JavaScript/TypeScript, or C#
Target Audience
Designed for experienced software engineers, tech leads, and architects who want to operationalize AI coding assistance across individual and team workflows. Ideal for engineering managers, DevOps, and QA leaders evaluating standardization and governance for AI-assisted development. Participants should be comfortable with Git, modern IDEs, and collaborating on mid-to-large codebases; no prior Cursor experience required.
Description
This hands-on course shows professional developers how to turn Cursor AI into a scalable productivity engine. You’ll go from setup and model tuning to deep mastery of context-aware completions, prompt engineering, and large-codebase strategies. We’ll design end-to-end workflows for scaffolding, debugging, refactoring, optimization, and documentation—then elevate them to team level with shared configurations, review practices, and governance. You will also extend Cursor with custom commands and plugins, diagnose performance bottlenecks, and apply QA guardrails to ship faster with confidence. The outcome: higher throughput, fewer defects, and consistent, repeatable engineering workflows that drive business results.
Learning Objectives
- Install and configure Cursor AI, set up workspaces, and integrate it with existing projects and version control.
- Navigate the interface confidently; tailor AI model selection and settings to match task, language, and codebase needs.
- Leverage context-aware, multi-line, and function-level completions to accelerate delivery while maintaining code style.
- Apply effective prompting and context management techniques to get precise, reliable outputs on large codebases.
- Build AI-assisted workflows for scaffolding, debugging, refactoring, optimization, and documentation generation.
- Standardize team practices: share AI configurations, enable review workflows, and enforce coding standards at scale.
- Extend and customize Cursor with commands, shortcuts, and plugins; profile performance and troubleshoot issues.
- Implement quality assurance guardrails and metrics; plan next steps for sustainable AI-assisted development.
Training Materials
Comprehensive courseware is distributed online at the start of class. All students receive a downloadable MP4 recording of the training.
Software Requirements
Students may choose to simply watch the instructor or follow along. If students choose to follow along, they will need to install Cursor AI and have access to a programming project for hands-on exercises.
Training Topics
Introduction to Cursor AI
- What is Cursor AI?
- Comparison with other AI coding assistants
- Key features and capabilities
- Installation and setup
Getting Started with Cursor
- Interface overview and navigation
- Workspace configuration
- AI model selection and settings
- Integration with existing projects
Advanced Code Completions
- Understanding Cursor's AI suggestions
- Context-aware code generation
- Multi-line and function-level completions
- Customizing completion behavior
Prompt Engineering for Cursor
- Effective prompting techniques
- Context management strategies
- Working with large codebases
- Optimizing AI responses
AI-Assisted Development Workflows
- Code generation and scaffolding
- Debugging with AI assistance
- Refactoring and code optimization
- Documentation generation
Team Collaboration with Cursor
- Sharing AI configurations
- Version control integration
- Code review workflows
- Team best practices
Advanced Features and Customization
- Custom commands and shortcuts
- Plugin integration
- Performance optimization
- Troubleshooting common issues
Conclusion and Best Practices
- Development workflow optimization
- Quality assurance with AI assistance
- Future of AI-assisted development
- Q&A and next steps