Agentic AI Full Course 2026 | Agentic AI Tutorial For Beginners | Agentic AI Course | Simplilearn

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This video on Agentic AI Full Course 2026 by Simplilearn will help you learn Agentic AI from beginner to advanced level and understand how autonomous AI systems can plan, reason, make decisions, and execute complex tasks with minimal human intervention. The course begins with an introduction to Agentic AI and explains how AI agents differ from traditional AI models by combining reasoning, planning, memory, tool usage, and goal-oriented execution. You will learn key concepts such as AI agents, large language models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), tool calling, agent workflows, multi-agent systems, memory management, and orchestration frameworks.

Following are the topics covered in the Agentic AI Full Course 2026

00:00:00 - Introduction To Agentic AI Full Course 2026
00:03:54 - Basics of Agentic AI
00:08:06 - Core Concepts of Agentic AI
00:15:15 - Agentic AI Frameworks & Libraries
00:22:09 - Memory and Long-Term Context
00:30:01 - Planning & Decision Chains
00:36:25 - Advanced Use-Cases of Agentic AI
00:39:48 - Agent Evaluation and Prompt Optimization
00:43:50 - Risks, Ethics, and Future of Agentic AI
00:47:27 - Hands-On Project
04:08:49 - Top Hacks To Speed Up Your AI Coding Workflow
05:51:53 - Generative Adversarial Tutorial
06:52:32 - Emergent AI App Builder Tutorial For Beginners
07:03:58 - Top 5 AI Automation Tools 2026
07:15:15 - How To Build WhatsApp AI Agent Using n8n
08:14:34 - Mobile App Development In 12 Minutes Using AI
09:40:37 - LangSmith Tutorial For Beginners 2026
10:14:58 - LangChain Tutorial For Beginners 2026
11:00:54 - LangGraph vs LangChain vs LangFlow vs LangSmith 2026
11:10:27 - Build LLM Apps Using Langchain
12:37:42 - Build a Chatbot Using Langchain
13:43:40 - What Is Miro And How To Use It?
13:59:30 - MetaGPT Tutorial For Beginners
14:56:55 - Streamlit Tutorial For Beginners
15:23:37 - Prompt Engineering Tutorial For Beginners
15:57:03 - LLM scale and deployment
16:07:26 - Large language models overview
16:14:53 - Features, tokens, and model choice
16:21:24 - AI tools across industries
16:26:32 - Resume and job matching demo
16:37:05 - Prompt engineering fundamentals
16:54:41 - Everyday prompt use cases
17:04:21 - Multimodal AI capabilities
18:19:50 - Key takeaways and next steps
18:26:41 - Effective prompt design principles
19:08:36 - Gen AI For Data Analytics
20:53:11 - Data integrity and EDA setup
21:42:42 - Data modeling with genAI
22:07:34 - Modeling techniques and use cases
23:46:43 - Future trends and wrap-up
24:03:57 - Gen AI Powered SQL For Data Analytics
25:09:42 - ER model fundamentals
26:26:15 - Database commands and basic setup
27:04:37 - Table creation and constraints
28:33:57 - Query logic and aggregation
29:00:27 - SQL functions introduction
30:19:37 - Using ChatGPT for SQL practice
30:22:09 - Agentic AI Projects For Beginners 2026
30:46:15 - What Is GenAI?
30:50:35 - How To Become Generative AI Engineer?
31:00:40 - Generative AI Vs Agentic AI Vs AI Agents
32:37:26 - LLM As Operating System
33:30:16 - LLM Benchmarking
34:46:06 - Prompt engineering with GPT-4
35:41:26 - Vibe coding tools comparison
36:06:01 - Generative AI learning roadmap
36:58:56 - AI for research and content
37:22:52 - Data insights and AI workflows
38:12:03 - Gemini CLI versus Claude Code
38:37:03 - ChatGPT attempts LeetCode problems
40:56:55 - Prompt library foundations
41:11:56 - Reasoning with o1 models
42:57:42 - Prompt library recap
43:56:35 - How To Build AI Automations Using n8n
44:26:47 - How To Build a Self Learning AI Agent
46:20:12 - Top 30 Generative AI Interview Questions 2026

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