Practical AI Agent Workflows with LLMs

Are you looking to build intelligent systems that can perform complex tasks autonomously? This course introduces you to the exciting world of AI agents, showing you how to leverage large language models (LLMs) to create dynamic and adaptive workflows. By understanding the core principles and modern techniques, you will gain the skills to develop agents capable of planning, acting, and observing their environment to achieve specific goals. Upon completing this course, you will be able to conceptualize, design, and implement practical AI agent workflows using current LLM capabilities, transforming your ability to automate processes and create more intelligent software solutions. What you'll learn: * Understand the foundational concepts and architectures of AI agents. * Learn effective prompt engineering strategies for guiding agent behavior. * Apply modern large language models, including function calling, to enable agent actions. * Build practical agentic workflows to automate multi-step tasks. * Explore techniques for equipping agents with external tools and knowledge. * Develop methods for evaluating and refining agent performance. This course begins with essential terminology and fundamental agent principles, then progresses to hands-on implementation with code snippets, demonstrating how to build agents that interact with tools and respond dynamically. You will learn to construct agentic loops and integrate various components for robust automation. This course is designed for absolute beginners with no prior experience in AI agents or advanced machine learning. All explanations start from first principles, making complex topics accessible. Start your journey into building intelligent AI agents today.