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Duration 21 hours
Course Outline
Foundations of AI-Enabled Development
- Definition and scope of AI-enhanced coding
- Key capabilities of the Cursor platform
- Role of large language models (LLMs) in the software engineering lifecycle
Initial Configuration of Cursor
- Deployment and environment setup procedures
- Establishing connections with GitHub and GitLab repositories
- Navigating the workspace interface and layout
Generating Code with Cursor
- Constructing prompts for generating new code segments
- Utilizing context-aware suggestions and auto-completion
- Standards for formulating effective prompts
Debugging and Error Remediation
- Applying AI support to debugging processes
- Detecting and addressing common technical defects
- AI-supported unit testing and error diagnostics
Refactoring and Documentation Maintenance
- Techniques for AI-directed code refactoring
- Automated generation of technical documentation
- Ensuring consistency across extensive project structures
Integration of Cursor with Development Ecosystems
- Interoperability with VS Code and terminal-based utilities
- Incorporating Cursor into CI/CD pipelines
- Facilitating team collaboration through AI-driven insights
Advanced AI-Driven Coding Processes
- Orchestrating multiple AI models for complex engineering tasks
- Tuning prompts and managing context windows
- Ethical, security, and compliance considerations in AI-assisted development
Conclusion and Subsequent Action Items
Requirements
- A foundational understanding of software development lifecycles
- Proficiency in programming with Python, JavaScript, or TypeScript
- Working familiarity with Git and standard code editors
Target Audience
- Software developers
- DevOps engineers
- Professionals focused on AI and automation initiatives
