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Duration 14 hours
Course Outline
Introduction to Devstral and Coding Agents
- Overview of the Devstral architecture
- Agentic AI concepts applied to software engineering
- Practical use cases for coding agents
Setting Up the Development Environment
- Installation and configuration of Devstral
- Integration with Python and Git workflows
- IDE support using Visual Studio Code
Designing Coding Agents
- Defining agent roles and core capabilities
- Workflow design for code navigation and refactoring
- Strategies for error handling and rollback
Tool and API Integration
- Connecting agents to essential developer tools
- API integration for accessing external services
- Automation patterns leveraging coding agents
Agentic Workflows in Practice
- Code exploration and automated documentation generation
- Assistance with automated refactoring and testing
- Collaborative coding processes involving agents
Security and Best Practices
- Establishing safe execution environments
- Managing access controls and permissions
- Monitoring and logging agent activities
Scaling and Maintaining Coding Agents
- Deploying agents across multiple teams and projects
- Maintaining and updating agent workflows over time
- Driving continuous improvement through feedback loops
Summary and Next Steps
Requirements
- Solid proficiency in Python
- Practical experience with software development workflows
- Familiarity with 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
