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Course Outline
Fundamentals of Devstral and Coding Agents
- Architectural overview of Devstral
- Concepts of agentic AI within software engineering
- Practical applications for coding agents
Preparing the Development Workspace
- Installation and configuration of Devstral
- Integration with Python and Git-based workflows
- Support within Visual Studio Code
Architecting Coding Agents
- Specifying agent roles and functional capabilities
- Workflow strategies for code navigation and refactoring
- Methods for error handling and rollback
Integrating Tools and APIs
- Linking agents to essential developer utilities
- API connections for external service interactions
- Automation patterns utilizing coding agents
Applying Agentic Workflows
- Code exploration and automated documentation creation
- Support for automated refactoring and testing
- Collaborative coding sessions with agents
Security Protocols and Best Practices
- Establishing safe execution environments
- Managing access controls and permissions
- Monitoring and logging agent activities
Scaling and Managing Coding Agents
- Deploying agents across various teams and projects
- Maintenance and updating of agent workflows
- Continuous refinement through feedback mechanisms
Conclusion and Future Directions
Requirements
- Proficient command of Python
- Practical experience with software development lifecycles
- Knowledge of API interactions and code integration
Target Audience
- Machine Learning Engineers
- Developer Tooling Teams
- SREs focused on enhancing developer experience
14 Hours
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny