Free 8-hour agentic AI course for beginners: generative AI, embeddings, LLMs, RAG agents, design patterns, agent frameworks, MCP, and guardrails.
Chapter 1
Outlines the course path from generative AI foundations through agents, frameworks, MCP, and guardrails.
Write one sentence describing an AI agent you would like to build by the end of the course.
The Agentic AI Full Course is a free, nearly 8-hour beginner course that takes you from generative AI fundamentals to building AI agents. It covers generative AI systems, embeddings, large language models, RAG agents, agentic design patterns, Amazon Q setup, agentic frameworks, the Model Context Protocol (MCP), and LLM guardrails. It suits beginners who want one structured path through the whole agentic AI stack.
The course follows the order in which the concepts build on each other. You start with how generative AI systems and embeddings work, move to how LLMs generate text and where they fail, then learn how RAG grounds answers in real data. From there you learn what makes AI agentic, the design patterns used to structure agents, and how frameworks, MCP, and guardrails turn those ideas into reliable applications.
It is one of the most complete free courses on agentic AI, covering foundations, retrieval, design patterns, frameworks, MCP, and safety in a logical order. Long sections are clearly split, which makes the course work well as a structured study path.
Agentic AI skills such as RAG, agent frameworks, MCP, and guardrails are in high demand for AI engineer, ML engineer, and GenAI developer roles. Completing this course and building a guarded RAG agent gives you both the vocabulary and a portfolio project for interviews.
This course was published by Intellipaat. Free Coding Academy curates and organises publicly available learning media for educational purposes and does not own, host, download, or re-upload the video.
Agentic AI refers to AI systems that can reason through a task, choose and use tools, and act with some autonomy, rather than only answering a single prompt. This course builds up to agentic AI from generative AI, embeddings, LLMs, and RAG.
Yes. It starts with the basics of generative AI systems, embeddings, and large language models before covering agents. Basic Python helps for the practical sections, especially the agentic frameworks module.
A RAG agent uses retrieval-augmented generation: it searches a knowledge source for relevant information, adds it to the prompt, and then generates an answer grounded in that content. This reduces hallucinations and lets the agent use private or up-to-date data.
Yes. There is a dedicated chapter on the Model Context Protocol, the standard for connecting AI apps to tools and data, and a final chapter on LLM guardrails and their types for building safer, more reliable AI applications.
The video runs about 7 hours 50 minutes. The agentic frameworks section alone is nearly three hours, so plan to study it over two or three weeks with practice between sessions.
Only for the short Amazon Q setup chapter. The rest of the course, including RAG, design patterns, frameworks, MCP, and guardrails, can be followed without AWS.
The course was published by Intellipaat. Free Coding Academy organises it into a structured learning page with chapter summaries and practice tasks, and links to the original lesson.
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