Certificates & Achievements

Successfully completed the Claude Code in Action course, gaining hands-on experience with advanced AI-powered development tools and workflows. This course provided a comprehensive overview of integrating coding assistants into real-world projects, focusing on practical applications, automation, and effective team collaboration using Claude Code.

Key Learnings:

• Understood the architecture of coding assistants and how AI interacts with codebases through tool integration.
• Explored Claude Code's tool use system for handling complex, multi-step programming tasks.
• Mastered context management techniques for effective project resource referencing and conversation flow.
• Extended functionality using MCP servers and integrated external tools for enhanced development workflows.

Participated in the HuggingFace MCP Gradio Hackaton, where I designed and implemented an innovative Formula-1 MCP server. This project showcased expertise in real-time data integration, interactive user interfaces, and advanced agent workflows.

Key Learnings:

• Formula-1 MCP Server: Implemented a Formula-1 MCP server with proper structure and error handling that demonstrates how to make Claude Code team-aware and workflow-intelligent
• Real-Time Data Processing: Integrated real-time Formula-1 telemetry and results data into the MCP workflow
• Gradio Interface: Built an interactive Gradio interface for live demonstration and user interaction
• Prompt Engineering: Developed custom prompts to optimize agent performance and ensure accurate workflow execution

Successfully completed the HuggingFace Model Context Protocol (MCP) course, mastering advanced concepts such as PR Agent Workflow Server and Smart PR Management. The course provided hands-on experience with both high-level concepts and low-level protocol details, enabling the creation of powerful AI applications through standardized context management.

Key Learnings:

• PR Agent Workflow Server: Built a functional server with proper structure and error handling that demonstrates how to make Claude Code team-aware and workflow-intelligent
• Smart PR Management: Implemented automatic PR template selection based on code changes using MCP Tools
• CI/CD Monitoring: Tracked GitHub Actions with Cloudflare Tunnel and standardized Prompts
• Team Communication: Sent Slack notifications demonstrating all MCP primitives working together
• Real-World Case Study: Implemented a practical scenario every development team faces: automating PR creation, monitoring GitHub Actions, and notifying team members

Successfully completed the DeepLearning.ai Model Context Protocol (MCP) course, gaining comprehensive knowledge of MCP's theoretical foundations and practical implementations. The course provided hands-on experience with both high-level concepts and low-level protocol details, enabling the creation of powerful AI applications through standardized context management.

Key Learnings:

• Protocol Fundamentals: Mastered MCP architecture including host, client, and server components and their interactions
• Tool Development: Created custom MCP tools and resources for enhanced AI capabilities
• Implementation: Gained experience with both local (stdio) and remote (HTTP/SSE) transport protocols
• Integration: Extended Claude Desktop's functionality by integrating community MCP servers
• Practical Application: Applied MCP concepts to enhance LLM capabilities through structured context management

Successfully completed the HuggingFace Model Context Protocol (MCP) course, mastering the standardized approach to integrating external data and tools with large language models. This comprehensive program provided hands-on experience with MCP SDKs and frameworks, enabling the creation of powerful, context-aware AI applications.

Key Learnings:

• MCP Fundamentals: Gained deep understanding of the Model Context Protocol standard and its role in AI application development
• Technical Implementation: Mastered MCP SDKs and frameworks for building context-aware AI applications
• Practical Applications: Developed real-world solutions using MCP to integrate external data sources and tools with LLMs
• Community Collaboration: Engaged with the MCP community, sharing projects and learning from industry implementations
• Best Practices: Learned to design scalable and maintainable AI applications using MCP standards

Successfully completed the HuggingFace AI Agents course, a comprehensive program that combines theoretical foundations with hands-on implementation of AI agents. Through this course, I gained practical experience with cutting-edge agent frameworks and contributed to the open-source AI community by sharing my work on the Hugging Face Hub.

Key Learnings:

• Core Frameworks: Mastered smolagents, LlamaIndex, and LangGraph for building sophisticated AI agents
• Agent Architecture: Designed and implemented autonomous agents with capabilities for complex decision-making
• Practical Implementation: Developed and deployed agents in real-world scenarios
• Community & Collaboration: Participated in challenges and engaged with the AI community
• Model Fine-tuning: Specialized in fine-tuning LLMs for function-calling and optimizing agent performance