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Duration 14 hours
Course Outline
Fundamentals of Devstral and Coding Agents
- An introduction to Devstral’s architectural components
- Core concepts of Agentic AI in the context of software engineering
- Key use cases for implementing coding agents
Establishing the Development Environment
- Installation and configuration of Devstral
- Integration strategies with Python and Git workflows
- Support and setup within Visual Studio Code
Architecting Coding Agents
- Defining specific agent roles and functional capabilities
- Designing workflows for code navigation and refactoring tasks
- Implementing error handling mechanisms and rollback strategies
Connecting Tools and APIs
- Linking agents to essential developer tools
- Integrating APIs for interaction with external services
- Leveraging automation patterns through coding agents
Practical Agentic Workflows
- Executing code exploration and automated documentation generation
- Assisting with automated refactoring and testing procedures
- Facilitating collaborative coding alongside agents
Security Considerations and Best Practices
- Creating safe execution environments
- Managing access controls and permission sets
- Monitoring and logging agent activities
Scaling and Sustaining Coding Agents
- Deploying agents across various teams and project scopes
- Maintaining and updating established agent workflows
- Driving continuous improvement via feedback loops
Conclusion and Future Directions
Requirements
- Proficient command of Python
- Practical experience with software development processes
- Working knowledge of APIs 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