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Duration 14 hours
Course Outline
Fundamentals of Devstral and Coding Agents
- An overview of the Devstral architecture
- Concepts of Agentic AI applied to software engineering
- Practical use cases for coding agents
Preparing the Development Environment
- Installation and configuration of Devstral
- Seamless integration with Python and Git workflows
- Utilizing Visual Studio Code for IDE support
Architecting Coding Agents
- Specifying agent roles and functional capabilities
- Designing workflows for code navigation and refactoring
- Strategies for error handling and rollbacks
Integrating Tools and APIs
- Linking agents to essential developer tools
- Connecting to external services via APIs
- Leveraging automation patterns with coding agents
Implementing Agentic Workflows
- Exploring code and generating documentation automatically
- Assisting with automated refactoring and testing
- Collaborative coding practices with agents
Security Standards and Best Practices
- Establishing safe execution environments
- Managing access controls and permissions
- Tracking agent actions through monitoring and logging
Scaling and Sustaining Coding Agents
- Distributing agents across various teams and projects
- Maintaining and evolving agent workflows
- Driving continuous improvement through feedback loops
Conclusion and Path Forward
Requirements
- Proficiency in Python
- Practical experience with software development lifecycles
- Knowledge of API structures and code integration techniques
Target Audience
- Machine Learning 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