Anthropic & Claude AI Mastery 🚀

About This Project

This repository is a hands-on, end-to-end course and project on Anthropic's Claude models, designed to demonstrate advanced AI engineering, prompt design, API integration, and workflow automation. It is structured to showcase practical skills for your portfolio and curriculum.

Official Course Link:
Claude with the Anthropic API (Skilljar)

Key Highlights:

• Claude API integration & automation
• Prompt engineering & evaluation
• Retrieval Augmented Generation (RAG)
• Tool use, multi-turn conversations, and structured data
• Model Context Protocol (MCP) and agent workflows
• Real-world exercises, quizzes, and project-based learning

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📚 Course Structure & Modules

1. Introduction

• Welcome, Anthropic overview, Claude model landscape

2. Accessing Claude with the API

• API setup, authentication, and requests
• Multi-turn conversations & chat exercises
• System prompts, temperature, streaming
• Controlling output, structured data
• Quiz & feedback
• 📁 Module 2: Accessing Claude with the API

3. Prompt Evaluation

• Evaluation workflows, test dataset generation
• Model-based grading (implemented)
• Code-based grading (completed)
• Practical eval exercises & quiz
• 📁 Module 3: Prompt Evaluation

4. Prompt Engineering Techniques

• Clarity, specificity, XML structuring
• Example-driven prompting
• Prompting exercises & quiz
• 📁 Module 4: Prompt Engineering Techniques

5. Tool Use with Claude

• Tool schemas, message blocks, tool results
• Multi-turn & batch tool use
• Structured data, text edit, web search
• Tooling exercises & quiz
• 📁 Module 5: Tool Use with Claude

6. Retrieval Augmented Generation (RAG)

• Chunking, embeddings, RAG pipeline
• BM25, multi-index, reranking
• Contextual retrieval & quiz
• 📁 Module 6: Retrieval Augmented Generation

7. Features of Claude

• Extended thinking, image & PDF support
• Citations, prompt caching, code execution
• Features quiz
• 📁 Module 7: Features of Claude

8. Model Context Protocol (MCP)

• MCP clients, tool/resource definition
• Server inspector, client implementation
• Prompts, review & quiz
• 📁 Module 8: Model Context Protocol

9. Anthropic Apps: Claude Code & Computer Use

• Claude Code setup, automation, debugging
• MCP server enhancements, computer use
• Apps quiz
• 📁 Module 9: Anthropic Apps

10. Agents and Workflows

• Agents, parallelization, chaining, routing
• Tools, environment inspection
• Workflows vs agents, quiz
• 📁 Module 10: Agents and Workflows

11. Final Assessment & Wrap Up

• Final project & assessment
• Course wrap up
• 📁 Module 11: Final Assessment

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🛠️ Project Structure

• main.py: All code examples, exercises, and project logic
• pyproject.toml: Dependencies and environment setup
• README.md: Course and project documentation
• Additional scripts/resources per module as needed

📖 Getting Started

1. Access the official course:
   • Claude with the Anthropic API (Skilljar)
2. Clone the repository:

   git clone <repo-url>
   cd <project-folder>

3. Install dependencies:

   pip install -r requirements.txt  # or use poetry/pipenv as per pyproject.toml

4. Run and explore:
   • Work through main.py and module scripts
   • Complete exercises and quizzes
   • Experiment with API integrations and workflows

💡 Technologies & Skills Demonstrated

• Python 3.10+
• Anthropic Claude API
• Prompt engineering & evaluation
• Retrieval Augmented Generation (RAG)
• Tool use & automation
• Model Context Protocol (MCP)
• Agent & workflow design
• API integration & best practices
• Project-based learning

🤝 Contributing

Contributions, suggestions, and improvements are welcome! Please open an issue or submit a pull request.

📬 Contact

For questions or feedback, open an issue or connect via LinkedIn.