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Duration 14 hours
Course Outline
Introduction
- Distinguishing between workflows and autonomous agents
- Architectural overview and common application scenarios
Claude API Essentials
- The Messages API, model selection, and configuration parameters
- System prompt design and structured data output
- Implementing streaming responses and robust error management
- Lab: Initial API integration exercise
Tool Utilization
- Defining tool specifications and data schemas
- The tool-use loop mechanism and error recovery strategies
- Lab: Developing an agent that interacts with internal company APIs
MCP and Agent Skills
- Understanding MCP servers and client interactions
- Leveraging existing MCP servers and developing a basic custom server
- Implementing Agent Skills for reusable domain expertise
- Lab: Linking an agent to an external data source
Claude Agent SDK
- Agent execution loops, session management, and context handling
- Configuring permissions, hooks, and subagents
- Lab: Creating a research and reporting agent
Cost, Quality, and Security
- Implementing prompt caching and managing token budgets
- Establishing guardrails and human-in-the-loop approval processes
- Conducting evaluations with a small test dataset
- Implementing comprehensive logging and monitoring
Transitioning to Production
- Deployment strategies and secure secret management
- Ongoing maintenance and version control practices
- Developing a roadmap for your specific use case
Requirements
- Familiarity with programming in Python or TypeScript
- Practical experience with REST API calls and JSON processing
- Fundamental knowledge of large language models
Target Audience
- Software engineers and data specialists integrating AI capabilities into products and internal solutions
- Solution architects assessing agent-based architectures
- Technical teams aiming to transition AI solutions from prototype 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