Library / Artificial Intelligence

AI fundamentals for Beginners - Learn LLM, Agentic AI, MCP

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About this course

Artificial Intelligence is no longer just for researchers and data scientists. Generative AI and Large Language Models (LLMs) are becoming part of everyday work — from writing and research to automation and intelligent agents. If you want to actually understand how today's AI systems work (not just use ChatGPT and hope for the best), this course gives you that foundation.

This is a beginner-friendly, hands-on introduction to modern AI — but don't mistake "beginner-friendly" for "surface-level.

" By the end, you'll have built a Retrieval-Augmented Generation (RAG) pipeline visually using Langflow, and built and deployed your own working MCP (Model Context Protocol) server with real OAuth authentication and API integration — two things most "intro to AI" courses never get close to.

Taught by a cloud architect, not just an AI enthusiast

This course is created by Himanshu Rana, a Cloud Solutions Architect with 16+ years delivering enterprise-grade solutions on AWS and Azure, and a Microsoft Certified Trainer. You're learning AI fundamentals from someone who's also spent a career building production systems — so the explanations are grounded in how this technology actually gets used, not just how it's marketed.

What you'll learn

Core foundations of Generative AI and how LLMs actually "think" and generate responses

Tokens, prompts, and how tokenization affects both output quality and API cost

Prompt engineering techniques to get consistent, reliable results from any LLMRetrieval-Augmented Generation (RAG) — the difference between traditional RAG and agentic RAG, and how to build a RAG pipeline visually using Langflow, no heavy coding requiredAI Agents: how they plan, reason, and use tools across vector stores, web search, and APIsModel Context Protocol (MCP) — the emerging standard for connecting AI models to real tools and systems, including hosts, clients, servers, an

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