AI Agents & Agentic AI: Build Intelligent AI Agents

About this course

Master AI Agents & Agentic AI — From Fundamentals to Real-World AI AutomationAI Agents and Agentic AI are transforming the way we build intelligent applications, automate workflows, and interact with Large Language Models (LLMs). This course provides a complete introduction to AI Agents, Agentic AI, Generative AI, LLMs, Prompt Engineering, RAG, AI Automation, agentic workflows, and Multi-Agent Systems — taking you from fundamental concepts to building practical AI agents.

You'll begin by understanding what AI Agents are, how they interact with their environments, and how autonomous agents make decisions using goals, reasoning, utility, learning, and optimization.

Next, you'll explore Large Language Models (LLMs) and understand how models such as GPT, Claude, Gemini, and Llama can act as the intelligence behind modern AI agents. You'll learn about tokens, context windows, temperature, memory limitations, prompting techniques, and the strengths and limitations of LLM-powered agents.

What You'll Learn

You'll explore Prompt Engineering for Agentic AI, including zero-shot and few-shot prompting, system prompts, role-based prompting, structured outputs, and techniques for creating reliable prompts for AI automation.

You'll then discover how AI agents move beyond simple conversations by using tools, function calling, memory, embeddings, vector databases, and Retrieval-Augmented Generation (RAG).

The course also introduces important agentic reasoning and workflow patterns, including:

• ReAct (Reasoning + Acting)Planning and task decomposition
• Reflection and self-correction
• Chain-of-Thought and Tree-of-Thought concepts
• Single-step and multi-step agents
• Tool-using AI agents
• Short-term and long-term memory

Build Your First AI Agent</

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