Do I need prior experience with AI tools to take this course?

No prior AI experience is required. But a working knowledge of one or more generative AI tools such as ChatGPT, Claude, or Microsoft CoPilot will be helpful.

What AI tools will I learn to use?

This course focuses on principles and frameworks that apply across AI platforms rather than specific proprietary tools. You'll learn evaluation criteria to select the right tools for your organization's needs.

Is this course suitable for non-technical professionals?

Yes, the course is designed for business professionals, managers, and analysts. While you'll learn technical concepts, the focus is on strategic implementation rather than coding or deep technical skills.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Building and Deploying GenAI Agents for Process Automation

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Building and Deploying GenAI Agents for Process Automation

This course is part of GenAI for Business Process Automation Specialization

Instructors: Paul Pardi

1,599 already enrolled

Included with

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4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Explain AI agent fundamentals and architecture components, including decision-making models, memory systems, and tool integration patterns
Build functional AI agents using no-code platforms to automate business processes with multi-step reasoning and context awareness
Describe best practices for deploying and scaling AI agents in production environments
Evaluate agent performance and business impact by analyzing workflow efficiency and recommending continuous improvements

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

13 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the GenAI for Business Process Automation 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 4 modules in this course

This course will give you the core skills you need to build and manage AI-powered agents that automate real business processes and deliver measurable results. You’ll learn how to spot the best opportunities for AI agent automation, design effective multi-step agent workflows, and connect intelligent systems that can scale with your organization.

The course also covers how to design agent architectures—with practical strategies for error handling, monitoring, and optimizing—so your automations stay reliable and effective. You’ll get hands-on experience coordinating multiple AI agents and services, building end-to-end workflows that streamline processes and minimize manual effort. Through guided practice and real-world scenarios, you’ll build the skills to select the right AI tools, track automation performance, and keep improving your systems for ongoing business value. By the end, you’ll be ready to lead AI agent automation projects, identify the best places to apply intelligent agents, and transform manual processes into scalable, adaptive agent-powered workflows.

Module details

This module introduces the fundamentals of AI Agents and their role in automating complex business processes. You will explore how AI Agents make decisions, adapt workflows dynamically, and optimize automation using intelligent decision-making models. You will learn to design AI-powered workflows, apply event-driven automation, and integrate AI decision processes to enhance efficiency and adaptability in real-world business environments.

What's included

7 videos4 readings4 assignments1 discussion prompt4 plugins

7 videosTotal 24 minutes

Welcome to GenAI Agents for Process Automation3 minutes
What Is an AI Agent?3 minutes
AI Agents vs AI-powered Automation3 minutes
AI Decision-Making Models4 minutes
AI Agent Decision Process3 minutes
The 5 Pillars of Agent Architecture4 minutes
Agent Tool Usage and Integration Patterns3 minutes

4 readingsTotal 18 minutes

Course Overview4 minutes
How to Succeed in This Course3 minutes
Helpful Tools and Resources5 minutes
Module Summary: Designing AI Agents for Complex Process Automation6 minutes

4 assignmentsTotal 54 minutes

Graded Quiz: Designing AI Agents for Complex Process Automation24 minutes
Practice Quiz: Foundations of AI Agents and Intelligent Automation10 minutes
Practice Quiz: AI Agent Decision-Making10 minutes
Practice Quiz: Agent Architecture and Components 10 minutes

1 discussion promptTotal 10 minutes

Designing an Agent with the Five Pillars in Mind10 minutes

4 pluginsTotal 47 minutes

Reading: Agent Ecosystem: Tools and Platforms Overview5 minutes
Reading: AI Memory and Context Awareness5 minutes
Reading: Agent State Management and Feedback Systems7 minutes
Lab: Design an Agent Blueprint30 minutes

This module focuses on hands-on development of functional AI agents using no-code platforms. You will build agents that demonstrate memory, tool integration, and multi-step reasoning capabilities. Through practical exercises, you'll learn to configure agent behavior, connect agents to business data sources, and program agent decision-making logic. You will practice using platforms like Zapier Agents to create working agents that can handle real business tasks autonomously.

What's included

6 videos1 reading4 assignments1 discussion prompt7 plugins

6 videosTotal 32 minutes

From Agent Design to Implementation6 minutes
Agent Development Lifecycle and Best Practices6 minutes
Programming Agent Memory and Context5 minutes
Agent Decision Trees and Logic Flows5 minutes
Agent Assembly: Bringing Architecture to Life5 minutes
Testing and Debugging Agent Behavior 6 minutes

1 readingTotal 4 minutes

Module Summary: Building Your First AI Agent4 minutes

4 assignmentsTotal 45 minutes

Graded Quiz: Building Your First AI Agent 15 minutes
Practice Quiz: Agent Development Platforms and Setup10 minutes
Practice Quiz: Agent Architecture Implementation10 minutes
Practice Quiz: Building and Testing Agents10 minutes

1 discussion promptTotal 10 minutes

AI Integration in the real world10 minutes

7 pluginsTotal 115 minutes

Reading: Platform Selection Criteria and Setup6 minutes
Reading: Agent Instruction Design and Prompt Engineering8 minutes
Lab: Discover Platform Features and Functions30 minutes
Reading: Agent Tool Integration Fundamentals5 minutes
Lab: Configure Your First Agent Setup30 minutes
Reading: Understanding Agent Data: JSON and API Basics6 minutes
Lab: Build and Test a Simple Agent30 minutes

This module covers the essential strategies for deploying, scaling, and optimizing AI Agents in real-world business environments. You will learn to transition AI-powered automation from development to production, scale AI workflows across teams and departments, and continuously improve performance using monitoring, debugging, and optimization techniques. Through hands-on exercises, you will explore best practices for AI deployment, workflow scaling challenges, and AI performance tuning to ensure efficient and effective automation.

What's included

6 videos1 reading4 assignments1 discussion prompt7 plugins

6 videosTotal 32 minutes

Preparing AI Agents for Deployment5 minutes
Best Practices for AI Deployment in Business6 minutes
Scaling AI Automation Across Teams and Departments6 minutes
Common Challenges in AI Scaling and Strategies to Overcome Them5 minutes
Monitoring AI Agent Performance and Debugging Workflows 5 minutes
Optimizing AI Automation for Efficiency 6 minutes

1 readingTotal 4 minutes

Module Summary: Deploying and Scaling AI Agents in Production4 minutes

4 assignmentsTotal 51 minutes

Graded Quiz: Deploying and Scaling AI Agents in Production21 minutes
Practice Quiz: Deploying AI Agents10 minutes
Practice Quiz: Scaling AI Agents10 minutes
Practice Quiz: Optimizing AI Agent Performance 10 minutes

1 discussion promptTotal 10 minutes

Designing for Failure: Building Resilient Agents10 minutes

7 pluginsTotal 92 minutes

Reading: AI Deployment Models and Strategies6 minutes
Reading: Python Scripting for Agent Management7 minutes
Reading: Strategies for Scaling AI-Powered Agent Workflows8 minutes
Lab: Design a Deployment and Scaling Strategy30 minutes
Reading: AI Performance Tuning and Continuous Improvement Strategies5 minutes
Reading: Agent Performance Metrics and KPIs6 minutes
Lab: Analyze AI Workflow Performance and Recommend Improvements30 minutes

In this final module, you will apply the knowledge gained in the course through a final project and a graded assessment. You'll demonstrate your ability to create an automated workflow from start to finish, take your final assessment, and prepare for continued learning in the field of AI automation.