
Guide for Agentic AI
This Agent AI tutorial and slides walks users through the process of designing, building, and deploying AI agents to perform autonomous tasks. It begins with an introduction to the foundational concepts, such as autonomy, decision-making, and reinforcement learning, and explains how agents interact with their environment and achieve goals. The tutorial then delves into practical implementation, covering key steps like defining the agent's objectives, designing workflows, integrating APIs and tools, and training the agent using data. It also explores advanced topics like multi-agent systems, personalization, and continuous learning. Practical exercises often include building a basic AI agent, such as a chatbot or task automation bot, and gradually advancing to more complex use cases like dynamic planning or real-time decision-making. Tutorials emphasize debugging, testing, and monitoring to ensure reliability, and may include discussions on best practices for ethics, transparency, and data privacy. By the end, learners gain hands-on experience and a clear understanding of deploying AI agents in real-world scenarios.