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This video on Generative AI Full Course 2026 by Simplilearn will help you learn generative AI from beginner to advanced level and understand how AI models create text, images, and content using modern machine learning techniques. The course begins with an introduction to generative artificial intelligence and explains how large language models and deep learning work. You will learn key concepts such as prompt engineering, model training basics, and how AI generates human-like responses. The tutorial covers popular tools and platforms like ChatGPT and other generative AI applications used in real-world scenarios. You will understand use cases of generative AI in content creation, coding, marketing, automation, and business productivity. The course also explains AI limitations, ethical considerations, and responsible AI usage. You will learn how businesses use generative AI to improve efficiency and innovation. By the end of this generative AI tutorial for beginners, you will clearly understand generative AI concepts, tools, and skills needed to start a career in AI and build real-world applications.

Following are the topics covered in Generative AI Full Course 2026:

00:00:00 - Introduction to Generative AI Full Course 2026
00:03:49 - What Is GenAI?
00:08:09 - How To Become Generative AI Engineer?
00:11:12 - What Is Generative Artificial Intelligence?
00:15:44 - AI vs Generative Ai vs Agentic AI vs AI Agents: Key Differences Explained In Detail
00:48:43 - Generative AI Vs Agentic AI Vs AI Agents
01:01:26 - Gen AI Engineer Roadmap For 2026
01:06:16 - Generative AI For Beginners
02:18:14 - LangChain Tutorial for Beginners
03:00:31 - LangGraph vs LangChain vs LangFlow vs LangSmith 2026
03:10:04 - How To Run LLM Models Locally
03:17:19 - LLM As Operating System
04:10:09 - LLM Benchmarking
04:16:43 - Build LLM Apps Using Langchain
05:43:58 - Build a Chatbot Using Langchain
06:49:56 - LLM Prompting With Gemini
07:34:22 - Prompt Engineering Tutorial
07:37:30 - Prompt engineering fundamentals
07:59:12 - Prompt engineering with GPT-4
08:54:32 - Vibe coding tools comparison
09:03:53 - Context engineering explained
09:19:07 - Generative AI learning roadmap
09:25:02 - Multimodal prompting deep dive
09:45:34 - Generative AI foundations
09:57:54 - Prompting with generative AI tools
10:12:02 - AI for research and content
10:35:58 - Data insights and AI workflows
10:58:59 - Google Nano Banana demos
11:10:46 - Claude Code in the terminal
11:25:09 - Gemini CLI versus Claude Code
11:41:18 - ChatGPT for programming basics
11:50:09 - ChatGPT attempts LeetCode problems
13:16:30 - Google Flow video creation
13:59:09 - GitHub Copilot agent mode
14:10:01 - Prompt library foundations
14:25:02 - Reasoning with o1 models
15:26:26 - React e-commerce app with ChatGPT
15:58:32 - Prompt tuning overview
16:10:48 - Prompt library recap
16:24:59 - No-code AI workflow tools
16:39:10 - Generative AI For Data Analysis
16:50:38 - Future Of Generative AI
17:00:22 - Generative Adversarial Tutorial
17:00:22 - Zapier AI Tutorial For Beginners
17:09:41 - How To Build AI Automations Using n8n
17:39:53 - How To Build a Self Learning AI Agent
18:09:44 - Build and Automate AI Agents Using n8n
19:33:18 - Introduction To Agentic Workflow
21:03:31 - How to Build No Code AI Workflows
21:37:37 - Amazon BedRock Console Page
21:46:29 - AI WorkFlow
22:22:30 - AI Coding WorkFlow
22:35:07 - Generative AI Interview Questions and Answers

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