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Agents and Agentic AI: Fundamentals, Use Cases, and Tools

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Agents and Agentic AI: Fundamentals, Use Cases, and Tools

SkillUp

Instructor: SkillUp

Included with Coursera PlusLearn more

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Distinguish AI agents from chatbots, copilots, and traditional automation so you can judge what a tool really does

  • Describe how an agent’s goals, tools, memory, and feedback loops combine into patterns such as workflow and human-in-the-loop designs

  • Compare no-code agent-building tools and use cases to choose the right fit for your budget, skills, and work

  • Create an agent blueprint with objective, tools, workflow, approval steps, constraints, and success criteria for a task from your own work

Details to know

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Recently updated!

November 2026

Assessments

17 assignments¹

AI Graded see disclaimer
Taught in English

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Build your subject-matter expertise

This course is part of the AI Agents for Dummies Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

In this module, you will explore what sets AI agents apart from the generative AI tools you may already use. You will trace the shift from single-prompt interactions to multi-step, goal-driven agent behavior, and learn to place agents along a spectrum of autonomy, from fully human-driven to fully autonomous. Through a practitioner’s perspective, a hands-on classification activity, and grounded comparisons, you will build the vocabulary needed to recognize an agent when you see one, and to judge when agentic behavior is warranted. By the end of this module, you will be able to distinguish agents from chatbots and automation, and identify where agents fit relative to full automation and full human control.

What's included

3 videos8 readings3 assignments1 plugin

In this module, you will open up the AI agent to examine its core components: model, instructions, tools, memory, and feedback, and see how these pieces work together to complete multi-step tasks. You will then survey common agent patterns, including tool-using agents, workflow agents, human-in-the-loop agents, and multi-agent systems. A hands-on mapping activity lets you apply these concepts directly to a scenario. By the end of this module, you will be able to describe what an agent is made of, recognize the patterns those parts commonly form, and explain how components and patterns combine in practice.

What's included

3 videos4 readings4 assignments1 plugin

In this module, you will survey where AI agents create real value across productivity, operations, customer service, analysis, research, scheduling, and workflow automation, and build a working map of the tools available to build them. You will compare no-code workflow platforms, visual agent builders, open-source/community tools, and hosted AI assistants, and get a preview of Make as the course's recommended primary platform for later labs, with Zapier and open-source/community visual agent builders discussed as alternatives. A hands-on lab has you use an AI tool to choose and justify a tool for your own use case, carrying that choice into Module 4. By the end of this module, you will be able to identify strong agent use cases and select an appropriate tool category for a given need.

What's included

3 videos4 readings4 assignments

In this module, you will apply everything from the course so far to design your own agent, without building it yet. You will select and scope a use case, then construct an Agent Use-Case Blueprint that defines the objective, tools, workflow mapping, approval steps, constraints, and success criteria, while accounting for the data and permission considerations any real agent design must address. A hands-on lab has you draft the blueprint and use an approved AI tool to critique and refine it before the graded final project and peer review in Module 5. By the end of this module, you will have a complete, defensible blueprint ready to build in Course 2.

What's included

2 videos5 readings4 assignments

In this final module, you will finalize the Agent Use-Case Blueprint you began drafting in Module 4, applying the full course's concepts to a complete, submission-ready design. The project assesses your ability to integrate knowledge from all four content modules into one coherent, defensible agent design. The module then closes with a course summary, glossary of key terms, and a final exam covering the course as a whole. Learners will also evaluate the completed blueprint against feasibility, value, safety, and human oversight criteria and identify any revisions needed before final submission.

What's included

1 video6 readings2 assignments

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.