Agentic AI Full Course 2026 | Agentic AI Tutorial For Beginners | Agentic AI Course | Simplilearn
At a glance
- Length
- 1 hr 11 min
- Channel
- Simplilearn
- Video from
- Feb 2026
- Rating
- ⭐⭐ Great video · 2/2
- Best for
- Developers and professionals entering agentic AI without prior background
What this video answers
- What is the difference between agentic AI and traditional AI models?
- What are AI agent workflows, and why do they matter?
- Which frameworks and libraries does the course recommend?
- How do AI agents maintain long-term context?
- Will this course teach me to build my own AI agent?
What This Agentic AI Course Covers for Beginners
Simplilearn's Agentic AI Full Course 2026 is a structured tutorial designed to take newcomers from foundational concepts to hands-on application of autonomous AI systems. The course walks through how modern AI agents differ from traditional models, then progresses into the mechanics of how these systems plan, decide, and automate workflows without step-by-step human direction.
The tutorial spans nine chapters, starting with introductory material and building toward practical implementation. Rather than staying purely theoretical, it includes real-world use cases, implementation frameworks, and a capstone project. The pacing suggests it's built for viewers with little to no prior agentic AI experience, though comfort with general tech concepts would help.
Key Moments
Notable Strengths and Gaps in This Tutorial
- Covers both foundational theory and frameworks—chapters range from core concepts to specific tools and libraries, giving learners vocabulary and practical options.
- Addresses memory and context retention in agents, a feature that distinguishes agentic systems from simpler AI tools and matters in real applications.
- Includes ethics and risk discussion late in the course, acknowledging concerns around autonomous systems rather than glossing them over.
- Concludes with a hands-on project, pushing beyond passive learning into building something tangible.
- Nine structured chapters with timestamps make it easy to skip around or revisit sections without rewatching the entire video.
- No prerequisites stated, though the description targets "beginners"—this could mean the bar is accessible but may move quickly through certain topics for absolute newcomers.
Who Should Watch This Agentic AI Tutorial
This course suits developers, business analysts, and technology professionals who want to understand how AI agents work and where they fit into modern workflows. If you're evaluating whether agentic AI is relevant to your role or considering a career shift into applied AI, the broad curriculum gives enough context to make an informed decision.
It's less useful if you're already deep into agentic frameworks or looking for advanced optimization techniques. The verdict: worthwhile for anyone transitioning into AI roles or upgrading their technical literacy around next-generation AI capabilities, especially if you're the type who learns best from structured video with clear chapter breaks.
Common Questions About Agentic AI Fundamentals
What is the difference between agentic AI and traditional AI models?
Traditional AI models respond to input; agentic AI systems can plan multi-step tasks, choose tools, and make decisions autonomously. The video distinguishes this distinction early to set expectations for what learners will study.
What are AI agent workflows, and why do they matter?
Agent workflows are the sequences of actions an AI system takes to reach a goal—planning, tool selection, execution, and adjustment. The tutorial covers these because they're central to how autonomous systems operate in practice.
Which frameworks and libraries does the course recommend?
The video has a dedicated chapter on agentic AI frameworks and libraries, though the description doesn't name specific tools. You'll need to watch that section to see which options the instructor emphasizes for beginners.
How do AI agents maintain long-term context?
A full chapter covers memory and long-term context—how agents retain information across multiple interactions or tasks. This prevents agents from "forgetting" earlier steps and is essential for multi-turn workflows.
Will this course teach me to build my own AI agent?
Yes. The final chapter is a hands-on project, and earlier sections cover prompt engineering and automation principles needed to create agent-powered applications, though the specific scope of the project isn't detailed in the description.
Key Terms
- Agentic AI
- An artificial intelligence system that can autonomously plan, make decisions, and execute multi-step tasks with minimal human intervention.
- AI agent workflows
- The sequences of actions and decisions an AI system follows to accomplish a goal, including tool selection and task execution.
- Prompt engineering
- The practice of crafting input instructions or questions to guide an AI model toward desired outputs and behaviors.
- Long-term context
- An agent's ability to retain and reference information across multiple interactions or steps rather than treating each request independently.
- Agent evaluation
- The process of testing and measuring how well an AI agent performs its intended tasks and achieves its goals.
📚 Go deeper: Prompt engineering explained
Sources: Agentic AI · AI agent workflows · Prompt engineering · Long-term context · Agent evaluation — definitions cross-referenced with Wikipedia
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Description
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This Agentic AI Full Course 2026 by Simplilearn is designed to help beginners understand how modern AI systems can plan tasks, make decisions, and automate workflows. The course starts with the basics of Agentic AI, how it works, and how it is different from traditional AI models. You will then learn about AI agents, agent workflows, tools, and real-world use cases in simple terms. The course also introduces concepts like prompt engineering, automation, and building AI-powered applications. As you progress, you will explore practical examples and future trends of autonomous AI systems. This course is ideal for anyone who wants to understand next-generation AI technology and how it can be used in real business and development scenarios.
Following are the topics covered in the Agentic AI Full Course 2026:
00:00:00 - Introduction To Agentic AI
00:03:11 - Chapter 1: Basics of Agentic AI
00:08:06 - Chapter 2: Core Concepts of Agentic AI
00:15:15 - Chapter 3: Agentic AI Frameworks & Libraries
00:22:09 - Chapter 4: Memory and Long-Term Context
00:30:01 - Chapter 5: Planning & Decision Chains
00:36:25 - Chapter 6: Advanced Use-Cases of Agentic AI
00:39:48 - Chapter 7: Agent Evaluation and Prompt Optimization
00:43:50 - Chapter 8: Risks, Ethics, and Future of Agentic AI
00:47:27 - Chapter 9: Hands-On Project
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➡️ About Applied Generative AI Specialization
The Applied Gen AI Course equips learners with the skills to build AI-driven solutions. Learn to design, train, and deploy models while addressing ethics, bias, and compliance. Gain industry-relevant experience through hands-on projects to drive innovation and stay competitive in an AI-powered world.
Key Features
✅ Get a program completion certificate from Michigan Engineering Professional Education
✅ Engage in 70+ hours of live online sessions led by industry experts
✅ Access a comprehensive curriculum covering Python, AI literacy, and GenAI principles (VAEs, GANs, and LLMs)
✅ Explore agentic frameworks and create adaptive AI agents using LangChain
✅ Implement advanced prompt engineering, RAG, and fine-tune models for domain-specific AI solutions
✅ Apply best practices for AI transparency, fairness, security, and regulatory compliance
✅ Work with 12+ modern AI tools, including OpenAI, Stable Diffusion, Microsoft Copilot, and Streamlit
✅ Earn a course completion certificate hosted on the Microsoft Learn portal for Microsoft courses
✅ Experience flexible learning with session recordings
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Gain 24/7 access to Simplilearn’s Learning Management System (LMS)
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