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Duration 14 hours
Course Outline
Fundamentals of Devstral and Autonomous Coding Agents
- Architectural overview of the Devstral framework.
- The role of Agentic AI concepts in software engineering.
- Strategic use cases for implementing coding agents.
Development Environment Configuration
- Installation and precise configuration of Devstral.
- Alignment with Python and Git-based workflows.
- Optimizing IDE support within Visual Studio Code.
Architecting Coding Agents
- Defining specific agent roles and operational capabilities.
- Designing workflows for intelligent code navigation and refactoring.
- Implementing robust error handling and rollback mechanisms.
Integration of Tools and APIs
- Connecting autonomous agents to essential developer utilities.
- API integration for leveraging external services.
- Advanced automation patterns driven by coding agents.
Practical Agentic Workflows
- Deep code exploration and automated documentation generation.
- Supporting automated refactoring and testing processes.
- Facilitating collaborative coding sessions with agent assistance.
Security Protocols and Industry Best Practices
- Establishing safe and isolated execution environments.
- Managing access controls and permission hierarchies.
- Comprehensive monitoring and logging of agent activities.
Scalability and Long-Term Maintenance
- Deploying agents across distributed teams and diverse projects.
- Sustaining and evolving agent workflows over time.
- Driving continuous improvement through feedback loops.
Conclusions and Future Roadmap
Requirements
- Proficiency in the Python programming language.
- Practical experience with modern software development lifecycles.
- Working knowledge of API structures and code integration patterns.
Target Audience
- Machine Learning Engineers.
- Teams focused on developer tooling and infrastructure.
- SREs dedicated to optimizing the 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
