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Duration 14 hours
Course Outline
Introduction to Devstral and Coding Agents
- High-level view of Devstral architecture
- The role of Agentic AI concepts in software engineering
- Key use cases for deploying coding agents
Configuring the Development Environment
- Installation and configuration of Devstral
- Integrating with Python and Git workflows
- IDE integration using Visual Studio Code
Architecting Coding Agents
- Defining agent roles and specific capabilities
- Designing workflows for code navigation and refactoring
- Strategies for error handling and rollback
Integrating Tools and APIs
- Linking agents with external developer tools
- Connecting APIs for third-party services
- Automation patterns facilitated by coding agents
Applying Agentic Workflows in Practice
- Automated code exploration and documentation creation
- Assisted automated refactoring and testing
- Collaborative coding sessions with AI agents
Security Protocols 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 multiple teams and projects
- Maintaining and updating agent workflows
- Implementing continuous improvement through feedback loops
Summary and Future Steps
Requirements
- A solid grasp of Python programming
- Practical experience with standard software development workflows
- Proficiency in 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
