Agentic AI Full‑Stack Masterclass: RAG, MCP & AI Agents
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Unclaimed ProfileThe Agentic AI Full-Stack Masterclass represents a comprehensive guide for developers looking to move beyond simple chatbot APIs and build fully autonomous, production-grade AI systems. Led by creator Nikhil Agarwal, this masterclass focuses on the intersection of modern full-stack development and cutting-edge artificial intelligence, utilizing a robust stack that includes Angular, Node.js, Express, and leading LLM architectures from OpenAI and Google Gemini. Participants will dive deep into the Model Context Protocol (MCP), learning how to design and deploy custom MCP servers that grant large language models real-world tool execution capabilities. The curriculum thoroughly addresses Retrieval-Augmented Generation (RAG), guiding learners through embedding generation, semantic vector searches with databases like ChromaDB and pgVector, and manual cosine similarity implementations. By building a complete streaming chat interface in Angular, developers learn how to handle real-time data flow, render Markdown, and display intermediate tool execution outputs. This course is ideal for full-stack software engineers, system architects, and AI enthusiasts who want to master practical, end-to-end AI agent deployment rather than just theoretical concepts.
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Nikhil Agarwal is a software engineer and educator dedicated to demystifying modern artificial intelligence integration for full-stack developers. As the driving force behind Coding Technyks, Nikhil specializes in bridging the gap between theoretical AI concepts and production-ready applications. His teaching philosophy centers on project-based learning, guiding students through the complexities of Agentic AI, Retrieval-Augmented Generation (RAG), and the Model Context Protocol (MCP). Nikhil believes that the best way to master software engineering is by building real-world systems from scratch. In his courses, he breaks down sophisticated architectural patterns into manageable, step-by-step implementations, ensuring developers understand not just the "how" but…Show more
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Program Overview
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Learning format
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Price
Price may change · updated within 1–2 weeks
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What You'll Learn
- Architect and build a complete Full-Stack Agentic AI application using Angular, Node.js, and Express.
- Implement advanced Retrieval Augmented Generation (RAG) pipelines with embeddings, vector search, and context augmentation.
- Master the Model Context Protocol (MCP) by building custom MCP Servers in Node.js to expose real-world tools to LLMs.
- Build a production-ready Chat Interface in Angular that handles streaming responses, Markdown rendering, and tool outputs.
- Set up and manage Vector Databases (ChromaDB and pgVector) to store high-dimensional embeddings for semantic search.
- Create Static RAG Systems using JSON and math-based Cosine Similarity to understand the core algorithms of retrieval.
- Implement Native Tool Calling with Gemini and OpenAI to turn natural language into executable code functions.
- Connect your RAG Engine as an MCP Tool, creating a modular system where Agents can "choose" to search your database.
- Implement MongoDB integration from schema design to optimized query execution within a production-grade Angular and Node.js architecture.
Best For
- Full-stack developers aiming to transition into building autonomous agentic AI systems.
- Software engineers looking to master RAG pipelines and vector database integration.
- Tech professionals wanting hands-on experience with the Model Context Protocol (MCP).
- Developers proficient in JavaScript/TypeScript who want to build real-time streaming AI interfaces.
Not For
- Complete programming beginners who lack fundamental knowledge of Node.js and web development.
- Data scientists seeking a deep academic, mathematical focus on neural network architecture.
- Users looking for a non-technical introduction to AI tools without writing production code.
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