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AI fundamentals for Beginners - Learn LLM, Agentic AI, MCP (Udemy.com)

From Zero to AI-Ready 2026: Learn from scratch about Gen AI, LLMs, Prompt Engineering, RAG, MCP, Claude and AI Agents

Created by: Himanshu Rana

Last updated September 2026

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What you will learn

  • Fundamentals of Generative AI and how it differs from traditional AI
  • How Large Language Models (LLMs) work at a high level (without heavy math)
  • Prompt Engineering techniques to get better, more reliable AI outputs
  • How AI systems use context, memory, and tools
  • Build an AI agent and host in AWS Bedrock AgentCore that can get I.T done with simple prompting
  • Building own MCP server
  • Model Context Protocol (MCP) – how models securely connect to tools, data, and services
  • Using 3rd party MCP servers to connect to external systems
  • Working with open source model locally on your own machine
  • Building RAG based chatbots using Langflow
  • Build app using Claude Code

How it compares

Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:

  • Rating4.5 out of 5higher than 45% of them
  • Reviews1,308#337 of 1,183 by number of reviews
  • Length8.8 hourslonger than 66% of them
  • Last updatedSeptember 2026more recently than 96% of them

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Course Description

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 an AIOPS agent, 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 LLM

  • Retrieval-Augmented Generation (RAG) — the difference between traditional RAG and agentic RAG, and how to build a RAG pipeline visually using Langflow, no heavy coding required

  • AI Agents: how they plan, reason, and use tools across vector stores, web search, and APIs

  • Model Context Protocol (MCP) — the emerging standard for connecting AI models to real tools and systems, including hosts, clients, servers, and transport layers

  • Hands-on project: build your own MCP server to manage Google Calendar, with OAuth authentication and live API access — list, schedule, and delete events through an AI client

  • How to run and compare open-source models locally, and build an agentic AI Agent with AWS Bedrock AgentCore

  • How you can better use Claude features - Claude Code, Claude Cowork, Claude Skill

Who this course is for

  • Beginners with no prior AI or machine learning background who want a real foundation, not just buzzwords

  • Developers and non-developers alike who want a visual, low-code way to understand RAG and agentic workflows before diving into code-first frameworks like LangChain or LangGraph

  • Product managers, founders, and team leads who need a working mental model of how modern AI systems are built

  • Anyone curious about AWS Bedrock Agentcore, MCP, Langflow, or what it actually takes to connect an AI model to a real external tool

A note on scope

This course is intentionally focused — it's the solid on-ramp before you commit to a multi-week, multi-framework bootcamp. You'll walk away with real conceptual depth, a working RAG pipeline built visually in Langflow, and a complete hands-on MCP project — not a half-finished tour through ten different agent frameworks. If you're looking for a clear, practical starting point in AI before specializing into code-heavy frameworks, this is built for exactly that.

By the end of this course, you won't just know about AI — you'll know how it works under the hood, and you'll have built something real with it.


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Instructor Details

Himanshu Rana

Himanshu is a seasoned Cloud Consultant and Architect with 16+ years of experience designing enterprise-grade solutions on Microsoft Azure and AWS. He has led diverse projects for global clients and top-tier MNCs, specializing in scalable cloud infrastructure, security, and modernization.

A Microsoft Certified Trainer since 2011, Himanshu blends deep technical expertise with a passion for teaching. As a Udemy Instructor Partner, he has empowered over 50,000+ learners worldwide to upskill in Cloud and AI technologies through his bestselling, hands-on courses.

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Reviews

4.5

1,308 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Tousif Ahmed on 9/9/2026

Fantastic course!!! Basic concepts are all clearly explained, Expect a extended course to use the AI with coding.

By Thirumoorthy Thirumoorthy on 9/4/2026

I have no idea above AI. I need to start learning with AI to understand the workflow behind the AI. After I able to Integrate AI into my everyday work task to automate the repetitive work and ready for future driven AI era. I hope in this course to understand every concepts and apply the knowledge into real work efficiently and consume to save hours.

By Tariq Abdulghani Hussein on 8/21/2026

bedrock section was boring sorry for that, the is too long for its content its just introduction to topics it can be done simpler, but it was informative and very useful thanks for sharing your knowledge with us.

By Joseph Ely on 8/13/2026

Learning a lot about AI and how it functions. Some of the end topics become a little complicated but not to the point I can't keep up. Good course to start with.

By Shubham Bachan Tiwari on 8/10/2026

today i have finish this course and the outcome is now i have complete picture of AI workflow .Thank You for this course

By Shaik Ahmmad on 6/20/2026

This course really helps to kick start with the fundamental of AI and a quick demonstrations to understand the AI in a broad way. Great Learning!

By Dawid Zieliński on 5/28/2026

There are things I really like and things that I don't like us much. Pros: - I can see that you know what you're talking about. I can see you've done that before. You have managed to build my trust in your capabilities. - I enjoy the selection of topics. It is a rather good overview of the fundamentals. - I enjoy parts that visualize solutions in diagrams and I also enjoy examples - makes it easier to understand the concept. - I can really say that I got quite a good idea of a lot of AI related topics in 5 hours - 4 hours of your course + 1 hour of additional reading (googling / gemini). I definitely do not regret how as I have spent my time as an absolute beginner in this dark matter. Cons: - Course description does not say it's so heavy on the technical aspects. The fact that they're in there and the idea of setting solutions by yourself does not bother me at all - but the incosistency does, as I was looking for a theoretical course, not a practical one. No regrets on my side, but still, could be revamped. - The approach of starting with setting something up and then going to the course roadmap followed by theory does not chime well with me. It's difficult to do stuff and understand what you're doing without basic knowledge. The combo of multiple theory-practice segments is what works best for me and that is what you do later in the course anyway. But maybe that's me. - Some parts of the course, especially the latter parts, seem a bit improvised. Feels like you wanted to record long sequences in one take and maybe even prepared a draft scenario, but the tempo changes and it feels a bit chaotic. You do get your point across, but it broke my focus multiple times. - Again, about the latter part of the course, there are parts where you are reading parts of documentation. I can do that myself. The previous parts were better prepared with slides that had a limited amount of information in a bigger font (sort of summarized knowledge and felt more like a lecture than an audiobook). - Please also keep in mind, that some people can go through courses (even if partially) on a small mobile device and maybe even on the move. That's where many of the above points come in - amount of information, font size, even flow, theory and practice separation. All in all - it's a good course and I've enjoyed it. Thank you for the experience!

By Anonymized User on 5/19/2026

Excellent beginner-friendly course on Generative AI, LLMs, Agentic AI, RAG, and MCP. The practical demos and clear explanations made complex concepts easy to understand. I especially enjoyed the hands-on sections with AWS Bedrock, Langflow, and MCP servers. Highly recommended for anyone starting their AI journey. Thank you.

By Septia Permana on 3/26/2026

An excellent course. With only 5 hours of learning material (as of March 2026), all the content is incredibly useful. Very effective and efficient. I highly recommend this course.

By Anonymized User on 2/28/2026

Really good course for anyone wanting to learn the basics of AI. With so many new terminology in the AI world such as LLM, RAG, MCP, Prompt engineering, Langflow, LangChain, Spring AI, Agentic AI, Gen AI, Vector Database etc., it is really difficult to know where to start with. For me this is the perfect starting course for anyone wanting to venture into AI and know the basics with a real hands-on feel.

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Overall Score : 90 / 100