Digital Twin I (RAG Solution)
This course centres on a live industry project where you design and deploy a "Digital Twin"—a personal AI agent capable of autonomously representing its creator in professional job interviews.
By leveraging Retrieval-Augmented Generation (RAG) and the Model Context Protocol (MCP), you will build a system that can semantically search its own professional history to provide factual, context-aware answers to recruiters and hiring managers.
You will move from theory to application by mastering the following technical domains:
- RAG Architecture: Implementing semantic search using vector databases to ground AI responses in factual studies and professional experiences.
- MCP Server Development: Building Model Context Protocol servers (using Next.js/TypeScript) to integrate local data with AI agents.
- Data Pipeline Engineering: Annotating, enriching, and embedding professional profiles (JSON) into vector storage.
- AI-Powered Workflow: Utilising VS Code Insiders and GitHub Copilot to drive development and simulate agentic behaviours.
- Team Collaboration: Managing a software lifecycle using GitHub for version control (Pull Requests, branches) and ClickUp for project management
20 Lessons
