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Duration 14 hours
Course Outline
Introduction
- Distinguishing between workflows and autonomous agents
- Overview of architecture and common application scenarios
Claude API Essentials
- The Messages API, available models, and key parameters
- Crafting system prompts and managing structured output
- Handling streaming responses and managing errors
- Practical Lab: Initial API integration
Tool Utilisation
- Creating tools and defining schemas
- Understanding the tool-use loop and strategies for error recovery
- Practical Lab: Building an agent that interacts with internal company APIs
MCP and Agent Skills
- Components of MCP servers and clients
- Leveraging existing servers and developing a basic custom server
- Implementing Agent Skills for reusable expertise
- Practical Lab: Connecting an agent to a specific data source
Claude Agent SDK
- Managing the agent loop, sessions, and context
- Configuring permissions, hooks, and subagents
- Practical Lab: Constructing a research and reporting agent
Cost, Quality, and Safety
- Implementing prompt caching and managing token budgets
- Establishing guardrails and human-in-the-loop approval steps
- Conducting evaluations with a limited test set
- Setting up logging and monitoring systems
Transitioning from Prototype to Production
- Deployment strategies and secure handling of secrets
- Maintenance practices and version control
- Developing a roadmap for participants' specific use cases
Requirements
- Proficiency in programming with Python or TypeScript
- Practical experience in interacting with REST APIs and processing JSON data
- A foundational understanding of large language models
Intended Audience
- Software developers and data engineers integrating AI functionalities into products and internal systems
- Solution architects assessing various agent architectures
- Technical teams seeking to transition from prototyping to production environments
Testimonials (3)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
