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Course Outline
Intro to AI-Assisted Development
- The concept of AI-assisted coding.
- A look at Cursor’s primary features.
- The role of LLM integration in software engineering.
Configuring Cursor
- Installing and setting up the Cursor environment.
- Linking with GitHub and GitLab platforms.
- Navigating the workspace and interface layout.
Leveraging Cursor for Code Generation
- Creating new code snippets using prompts.
- Receiving context-aware suggestions and auto-completions.
- Techniques for crafting effective prompts.
Debugging and Resolving Errors
- Applying AI assistance to troubleshoot issues.
- Detecting and fixing common coding problems.
- Conducting AI-guided unit testing and error analysis.
Refactoring Code and Documentation
- Techniques for AI-driven code refactoring.
- Automating the generation of documentation.
- Ensuring consistency across large-scale projects.
Integrating Cursor with Dev Tools
- Collaborating with VS Code and terminal utilities.
- Incorporating Cursor into CI/CD pipelines.
- Team collaboration using AI-generated suggestions.
Advanced AI Coding Workflows
- Combining AI models for complex coding challenges.
- Tuning prompts and managing context windows.
- Navigating ethical and security aspects of AI development.
Conclusion and Future Steps
Requirements
- A solid grasp of software development workflows.
- Proficiency in programming with Python, JavaScript, or TypeScript.
- Knowledge of Git and basic code editors.
Target Audience
- Software developers.
- DevOps engineers.
- Professionals interested in AI and automation.
21 Hours
