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Course Outline
Introduction to Devstral and Coding Agents
- Overview of Devstral's architecture
- Core concepts of agentic AI in software engineering
- Practical use cases for coding agents
Configuring the Development Environment
- Installation and setup of Devstral
- Integration with Python and Git workflows
- Support within Visual Studio Code
Architecting Coding Agents
- Specifying agent roles and functionalities
- Designing workflows for code navigation and refactoring
- Strategies for error handling and rollback
Tool and API Integration
- Linking agents to essential developer tools
- Connecting to external services via API
- Automation patterns leveraging coding agents
Agentic Workflows in Action
- Code exploration and generating documentation
- Supporting automated refactoring and testing
- Collaborative coding sessions with agents
Security and Best Practices
- Establishing safe execution environments
- Managing access controls and permissions
- Monitoring and logging agent activities
Scaling and Maintaining Coding Agents
- Distributing agents across teams and projects
- Maintaining and evolving agent workflows
- Continuous improvement through feedback loops
Summary and Next Steps
Requirements
- Proficient command of Python
- Practical experience in software development workflows
- Knowledge of APIs and code integration patterns
Target Audience
- Machine Learning Engineers
- Developer Tooling Teams
- SREs focused on 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