About Course
Generative AI Agents are specialized systems designed to perform tasks by combining large language models’ ability to generate and understand language with specific functionalities like retrieving information (usually with retrieval augmented generation, or RAG),interacting with tools, or automating workflows. These agents are increasingly being used in industries such as customer support, e-commerce, data analysis, and software development to streamline operations and solve complex problems.
This course provides a concise introduction to what Generative AI Agents are, how they work, and how they can be applied effectively. It breaks down the foundational concepts behind AI agents, including their core types:
- Tool Use Agents: Capable of interacting with external tools, such as calendars, spreadsheets, or APIs, to complete specific tasks.
- Observation-Based Agents: Designed to gather, process, and interpret data from their environment for informed decision-making.
- Code-Based Agents: Able to generate, debug, and execute code to assist in software development or automation.
- Retrieval-Augmented Generation (RAG) Agents: Combine AI generation with live information retrieval from databases or the web, ensuring up-to-date and context-aware responses.
Throughout the course, you will explore practical examples and case studies to understand how these agents are implemented in real-world scenarios.
By the end, you’ll have a working knowledge of Generative AI Agents, their capabilities and limitations, and how they can be aligned with specific business needs. This foundational understanding will allow you to discuss AI agent technologies with your team and assess their potential for improving operational efficiency in your organization.
