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Duration 14 hours
Course Outline
Foundations of Devstral and Coding Agents
- Architectural overview of Devstral
- Application of agentic AI principles in software engineering
- Practical use cases for coding agents
Preparing the Development Environment
- Installation and configuration of Devstral
- Integration with Python and Git workflows
- Support within Visual Studio Code IDE
Architecting Coding Agents
- Specifying agent roles and functional capabilities
- Workflow design focused on code navigation and refactoring
- Strategies for error management and rollback
Integrating Tools and APIs
- Linking agents to essential developer tools
- API connections for third-party services
- Automation techniques leveraging coding agents
Implementing Agentic Workflows
- Codebase exploration and automated documentation generation
- Support for automated refactoring and testing
- Collaborative coding dynamics with agents
Security Protocols and Best Practices
- Establishing safe execution environments
- Managing access controls and permissions
- Monitoring and logging agent activities
Scaling and Maintaining Coding Agents
- Rolling out agents across multiple teams and projects
- Maintaining and evolving agent workflows
- Driving continuous improvement through feedback loops
Conclusion and Future Directions
Requirements
- A robust command of Python
- Practical experience in software development processes
- Knowledge of API interactions and code integration
Target Audience
- ML engineers
- Developer tooling teams
- SREs focused on enhancing developer experience
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