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Duration 14 hours
Course Outline
Introduction to Devstral and Coding Agents
- Overview of the Devstral architecture
- Concepts of Agentic AI in software engineering
- Practical use cases for coding agents
Establishing the Development Environment
- Installation and configuration of Devstral
- Integration with Python and Git workflows
- IDE support via Visual Studio Code
Architecting Coding Agents
- Defining agent roles and capabilities
- Designing workflows for code navigation and refactoring
- Strategies for error handling and rollback
Tool and API Integration
- Linking agents to developer tools
- API integration for external services
- Automation patterns leveraging coding agents
Agentic Workflows in Action
- Code exploration and documentation generation
- Assistance with automated refactoring and testing
- Collaborative coding workflows with agents
Security and Best Practices
- Creating safe execution environments
- Managing access controls and permissions
- Monitoring and logging agent activities
Scaling and Maintaining Coding Agents
- Deploying agents across teams and projects
- Updating and maintaining agent workflows
- Continuous improvement through feedback loops
Summary and Next Steps
Requirements
- A solid grasp of Python
- Practical experience with software development workflows
- Knowledge of APIs and code integration processes
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