Anthropic Courses (original) (raw)
Claude with Google Cloud's Vertex AI
This comprehensive course covers the full spectrum of working with Anthropic models through Google Cloud's Vertex AI.
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About this course
Course Description
This course provides comprehensive technical training on integrating and deploying Claude AI models through Google Cloud's Vertex AI. Developers will learn to implement Claude's API capabilities, from basic request handling to advanced features including tool use, retrieval augmented generation (RAG), and the Model Context Protocol (MCP). The curriculum covers practical implementation patterns, performance optimization techniques, and production-ready workflows for building AI-powered applications.
What you'll learn
- Set up and configure Claude models through Google Cloud's Vertex AI
- Implement multi-turn conversations with proper message handling and context management
- Design and evaluate prompts using systematic testing workflows and automated grading techniques
- Apply prompt engineering principles including XML tag structuring, example-based learning, and output control
- Build tool-use implementations enabling Claude to interact with external functions and APIs
- Develop RAG pipelines using text chunking, embeddings, BM25 search, and contextual retrieval techniques
- Utilize advanced Claude features including vision capabilities, PDF processing, citation generation, and prompt caching
- Implement the Model Context Protocol for creating custom tools, resources, and prompt templates
- Configure and deploy Anthropic Apps including Claude Code for automated development tasks and Computer Use for UI automation
- Design agent-based workflows with parallelization, chaining, and routing patterns for complex AI systems
Prerequisites
- Proficiency in Python programming
- Experience with Google Cloud Platform
- Understanding of JSON data structures
Who this course is for
- Backend developers building AI-powered APIs and services
- Full-stack engineers integrating LLM capabilities into applications
- ML engineers implementing production AI systems
- DevOps professionals deploying and scaling Claude implementations
- Technical architects designing AI-enhanced system architectures
- Developers transitioning from other LLM providers to Claude
- Engineers working on document processing, code generation, or automation workflows
Curriculum
- Introduction
- Anthropic overview
- Overview of Claude models
- Accessing Claude with the API
- Course satisfaction survey
- Quiz on accessing Claude with the API
- Prompt evaluation
- Quiz on prompt evaluation
- Prompt engineering techniques
- Quiz on prompt engineering techniques
- Tool use with Claude
- Multi-turn conversations with tools
- Implementing multiple turns
- Tools for structured data
- Quiz on tool use with Claude
- Retrieval Augmented Generation
- Introducing Retrieval Augmented Generation
- Implementing the RAG flow
- A Multi-index RAG pipeline
- Quiz on Retrieval Augmented Generation
- Features of Claude
- Quiz on features of Claude
- Model Context Protocol
- Quiz on Model Context Protocol
- Anthropic apps - Claude Code and computer use
- Enhancements with MCP servers
- Parallelizing Claude Code
- Agents and workflows
- Parallelization workflows
- Quiz on agents and workflows
- Final assessment
- Wrapping up!
About this course
Course Description
This course provides comprehensive technical training on integrating and deploying Claude AI models through Google Cloud's Vertex AI. Developers will learn to implement Claude's API capabilities, from basic request handling to advanced features including tool use, retrieval augmented generation (RAG), and the Model Context Protocol (MCP). The curriculum covers practical implementation patterns, performance optimization techniques, and production-ready workflows for building AI-powered applications.
What you'll learn
- Set up and configure Claude models through Google Cloud's Vertex AI
- Implement multi-turn conversations with proper message handling and context management
- Design and evaluate prompts using systematic testing workflows and automated grading techniques
- Apply prompt engineering principles including XML tag structuring, example-based learning, and output control
- Build tool-use implementations enabling Claude to interact with external functions and APIs
- Develop RAG pipelines using text chunking, embeddings, BM25 search, and contextual retrieval techniques
- Utilize advanced Claude features including vision capabilities, PDF processing, citation generation, and prompt caching
- Implement the Model Context Protocol for creating custom tools, resources, and prompt templates
- Configure and deploy Anthropic Apps including Claude Code for automated development tasks and Computer Use for UI automation
- Design agent-based workflows with parallelization, chaining, and routing patterns for complex AI systems
Prerequisites
- Proficiency in Python programming
- Experience with Google Cloud Platform
- Understanding of JSON data structures
Who this course is for
- Backend developers building AI-powered APIs and services
- Full-stack engineers integrating LLM capabilities into applications
- ML engineers implementing production AI systems
- DevOps professionals deploying and scaling Claude implementations
- Technical architects designing AI-enhanced system architectures
- Developers transitioning from other LLM providers to Claude
- Engineers working on document processing, code generation, or automation workflows
Curriculum
- Introduction
- Anthropic overview
- Overview of Claude models
- Accessing Claude with the API
- Course satisfaction survey
- Quiz on accessing Claude with the API
- Prompt evaluation
- Quiz on prompt evaluation
- Prompt engineering techniques
- Quiz on prompt engineering techniques
- Tool use with Claude
- Multi-turn conversations with tools
- Implementing multiple turns
- Tools for structured data
- Quiz on tool use with Claude
- Retrieval Augmented Generation
- Introducing Retrieval Augmented Generation
- Implementing the RAG flow
- A Multi-index RAG pipeline
- Quiz on Retrieval Augmented Generation
- Features of Claude
- Quiz on features of Claude
- Model Context Protocol
- Quiz on Model Context Protocol
- Anthropic apps - Claude Code and computer use
- Enhancements with MCP servers
- Parallelizing Claude Code
- Agents and workflows
- Parallelization workflows
- Quiz on agents and workflows
- Final assessment
- Wrapping up!