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Course Outline

Foundations of AI-Enhanced Development

  • Survey of AI-assisted coding utilities and current industry trends
  • The position of Cursor within contemporary development ecosystems
  • Core productivity gains and associated safety protocols

Initial Setup with Cursor

  • Installation and configuration procedures for Cursor
  • Linking Cursor to Git and mainstream code repositories
  • Navigating the interface and understanding primary functionalities

Leveraging AI Code Completion and Inline Prompts

  • Utilizing context-sensitive code completions
  • Crafting effective prompts to enhance AI output quality
  • Calibrating AI behavior to adhere to project-specific standards

Intelligent Editing and Refactoring

  • Implementing AI-generated refactor and edit recommendations
  • Employing “Edit with AI” for swift code transformations
  • Sustaining code consistency and readability throughout changes

Chat Integration and Documentation Support

  • Using the embedded chat feature to comprehend code and debug issues
  • Creating and validating documentation with AI assistance
  • Addressing code challenges through contextual analysis

Responsible Usage and Verification of AI Outputs

  • Critically verifying correctness to prevent uncritical adoption
  • Applying best practices for version control and code review cycles
  • Maintaining security and compliance standards in AI-supported processes

Collaborative Workflows and Team Efficiency

  • Streamlining the onboarding process for new team members
  • Incorporating Cursor into established CI/CD pipelines
  • Refining shared configurations and collaborative editing practices

Expanding Cursor Capabilities and Ongoing Development

  • Connecting third-party plugins and external APIs
  • Staying adaptable to new Cursor features and updates
  • Investigating emerging trends in AI-driven software engineering

Conclusion and Future Directions

Requirements

  • Proficiency in fundamental programming principles
  • Practical experience with at least one language, such as Python, JavaScript, or Java
  • Comfortable navigation within a code editor or IDE

Target Audience

  • Junior software developers
  • Mid-level engineers aiming to incorporate AI coding assistants
  • Development teams transitioning to AI-enhanced workflows
 14 Hours

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