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

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

Rating: 4.4469 ratings3,919 students5 total hours37 lectures
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AI fundamentals for Beginners - Learn LLM, Agentic AI, MCP Beginner

Course facts

  • Last updated 03/2026
  • English English [Auto], Dutch [Auto] , 5 more
  • Instructor: Himanshu Rana
  • AI agents, automation and connected workflows

What you'll learn

Practical outcomes

  • 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
  • Building AI agents in AWS Bedrock Agent that can work autonomously
  • 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

Curriculum

7 sections • 37 lectures • 5h 0m total length

Getting first hand taste of Generative Ai on your local Machine7 lectures • 31min
  1. Jumping right into the World of Artificial Intelligence02:01
  2. Setting up Ollama on Mac & Windows for local testing08:33
  3. Build your first Ai application: English Tutor using Ollama04:38
  4. Explore NotebookLM from Google04:54
  5. Course Roadmap03:15
  6. Know your Instructor - Skip if its boring01:21
  7. Taking a look at some of the widely used Closed and Open source models06:24
Fundamentals of Generative AI & LLMs5 lectures • 33min
  1. Generative AI vs traditional AI04:33
  2. What are Large Language Models (LLMs)06:00
  3. How LLM works09:20
  4. What are Tokens05:53
  5. AI Jargons - Inference, Context Window, hallucinations, RAG07:43
Art of Prompt Engineering: Understanding And Crafting good Prompts8 lectures • 36min
  1. Why need to engineer a prompt?03:20
  2. Role of Temperature, Top-K, Top-P in Sampling Output13:25
  3. Components of Prompt06:21
  4. Zero Shot Prompting02:20
  5. One-Shot or Few-Shot Prompting02:23
  6. Chain-of-Thought or CoT Prompting01:45
  7. ReAct or Reason and Act Prompting02:19
  8. System, contextual and role prompting03:50
Agentic AI Fundamentals and Development7 lectures • 1hr 7min
  1. What is an AI Agent04:22
  2. Components of AI agent05:35
  3. AWS Bedrock Agent - A Serverless Service05:40
  4. Understanding our AIOPS agent Architecture and Pre-req02:37
  5. Setup the AWS CLI and AWS Credentials10:25
  6. Create an AIOPS AI agent in AWS Bedrock29:52
  7. Responsible AI Principles08:21
Understanding and Implementing Agentic RAG5 lectures • 1hr 25min
  1. Understanding Retrieval Augmented Generation (RAG)13:12
  2. Front Desk Agent Without RAG - Understanding the problem13:33
  3. Implementing RAG based Front Desk agent using Langflow24:47
  4. Traditional RAG vs Agentic RAG11:07
  5. Implementing Agentic RAG22:08
Fundamentals of Model Context Protocol (MCP) and Use4 lectures • 44min
  1. What is MCP – The Universal Connector for AI03:52
  2. Get the taste of Docker MCP server10:06
  3. Basic MCP Architecture08:49
  4. Build your own MCP server to manage Your Google Calendar21:15
Conclusion1 lecture • 4min
  1. Wrap-up04:11

Who it is for

  • Beginners with no prior AI or machine learning experience
  • Students curious about Generative AI and modern AI systems
  • Developers who want to understand LLMs, agents, and MCP concepts clearly
  • Professionals and entrepreneurs looking to upskill in AI

Course description

Overview

Artificial Intelligence is no longer just for researchers and data scientists. Tools powered by Generative AI and Large Language Models (LLMs) are rapidly becoming part of everyday work—from writing and research to automation and intelligent agents. This course is a beginner-friendly, hands-on introduction to modern AI, designed to help you understand how today’s AI systems work and how to use them effectively—even if you have no prior AI or machine learning background. You’ll start with the core foundations of Generative AI, learn how LLMs think and respond, master prompt engineering, and then move into practical, real-world concepts like Retrieval-Augmented Generation (RAG), AI agents, and the Model Context Protocol (MCP)—the emerging standard for connecting models with tools and systems. By the end of the course, you won’t just know about AI—you’ll know how to work with it. **Note: Built especially for beginners, this course delivers a solid foundation without overwhelming you with advanced concepts — keeping your learning simple, practical, and to the point.

How This Course Will Help You: After completing this course, you will be able to: Clearly explain how modern AI and LLM-based systems work Write effective prompts and interact confidently with AI tools Understand RAG and Agentic RAG, and what problem they solve Understand how AI agents and MCP-powered systems are built Make informed decisions when using or building AI-powered products Build a strong foundation that will help you to move into advanced AI, agents, or application development Whether your goal is learning, building, teaching, or leading AI initiatives, this course gives you the mental model you need.

Instructor

Himanshu Rana

Himanshu Rana Cloud Solutions Architect, Microsoft Certified Trainer 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.