AI Agents and Agentic AI with Python & Generative AI

Vanderbilt connects the agent concept with the tools and actions an application can perform. A conceptual framework precedes tool management and a discussion of how agent-driven software differs from a conventional workflow. This is a foundation before a more specialized architecture course.

What you will learn

• Distinguish a model response from an agent action.
• Describe the tools available to an agent.
• Organize an agent workflow using a conceptual framework.

Who this suits

Beginning agent learners; the provider states that no background is required.

Before you enroll

Python appears in the implementation context. Preview the coding exercises and check model-service access, tool permissions and any usage charges before following them.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Provider access terms can change; review them before paying.

Put it into practice

Design a small agent with one read-only tool. Log its requested actions and test a case where the information needed to answer is unavailable.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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