Detailed Course Outline
Module 1: Introduction to AI Agents
AI agents are becoming essential as you interact with technology that thinks, adapts, and supports complex tasks. Learning this helps you stay confident in a world where intelligent systems are reshaping workflows, automating decisions, and collaborating with humans. By knowing how agents operate and why they matter, you strengthen your ability to work with tools that increasingly influence products, services, and industries.
In this module, you explore what AI agents are, how they evolved, and how they differ from chatbots and LLMs. You also examine their core components, major frameworks, practical use cases, myths, and real-world case studies. The module walks you through agent ecosystems, design considerations, and hands-on activities so you can build, analyze, and apply agent-based systems with practical confidence.
Module 2: Core Concepts & Types of AI Agents
AI agents are becoming more advanced, and you benefit from knowing how they work so you can use them confidently in real projects. As these systems take on tasks that involve perception, reasoning, memory, and action, you gain an advantage by recognizing how they support real-world decisions, automate processes, and adapt to different environments. This helps you become more effective when designing, evaluating, or collaborating with AI-driven systems. In this module, you explore how AI agents are structured, the components that
power them, and the many types used across industries. You also learn how to match agents to use cases, study a real mental-health application, and complete hands-on activities that guide you through building practical agents. By the end, you work with architectures, capabilities, classifications, tools, and real implementation workflows
Module 3: Tools for Non-Coders
No-code AI tools are becoming essential as more roles rely on automation, faster execution, and scalable workflows. You benefit from knowing how these platforms work because they let you build intelligent solutions without technical barriers. Whether you want to streamline tasks, boost productivity, or experiment with AI-driven ideas, these tools give you the power to create real outcomes without writing a single line of code.
In this module, you explore leading no-code and low-code platforms, learn how visual workflows function, and work with tools like Flowise, Langflow, Relevance AI, Zapier, Ottogrid, and n8n. You dive into features, benefits, setups, comparisons, a real HR case study, and a hands-on exercise where you build an onboarding agent from scratch. By the end, you know how to design practical AI-powered flows using accessible, drag-and-drop systems.
Module 4: Building Simple Agents
Building simple AI agents matters because it opens the door for you to create practical automation without relying on programming skills. As AI-driven workflows continue to expand across industries, you gain the ability to solve real problems, streamline tasks, and improve daily operations using tools that make agent creation accessible. This empowers you to contribute to smarter solutions, experiment confidently, and design systems that deliver value in your own work.
In this module, you explore no-code platforms, build multiple AI agents, and work with tools like Relevance AI, n8n, Zapier, Flowise, and Langflow. You create agents for HR support, persistent memory conversations, automated email logging, and FAQ generation. You also learn troubleshooting methods, validation techniques, and complete a hands-on project to build a research assistant, giving you practical experience in designing end-to-end agent workflows.
Module 5: AI Agent Builder
Building skill in this area helps you excel in tasks that require multiple tools, structured workflows, and intelligent automation. As you explore real AI-driven processes, you gain the ability to execute complex goals, manage evolving constraints, and deliver reliable outcomes. This gives you an advantage in creating scalable solutions, improving decision-making, and designing systems that adapt to changing requirements across real-world scenarios.
This module equips you with the essentials of multi-tool agents, chaining methods, state management, prompt engineering, orchestration platforms, and multi-agent systems. You work through architectures, chaining patterns, advanced prompting techniques, practical case studies, and hands-on exercises such as building automated workflows using Make.com. Together, these sections prepare you to design, implement, and optimize powerful AI-driven workflows from end to end.
Module 6: Integration, Application Mapping & Deployment
AI agents only create real impact when you can turn them into reliable, secure, and accessible tools that users can interact with confidently. By learning how deployment, channels, hosting, data connections, and security work together, you give yourself the ability to build agents that scale, stay compliant, and perform well in real-world conditions. This helps you avoid common failures, reduce risks, and ensure your agents deliver measurable value across your organization.
In this module, you explore deployment steps, channel selection, hosting choices, data integration options, and security essentials. You also learn how to monitor agents, plan updates, and map different agent types to business scenarios. Each section guides you through practical elements—from connecting databases to applying authentication—so you can confidently deploy, maintain, and evolve AI agents across diverse environments.
Module 7: Monitoring, Guardrails & Responsible AI
AI agents can create powerful results, but they also introduce risks when left unchecked. As you work with autonomous systems, you need the ability to keep them safe, predictable, and aligned with real-world expectations. When you know how to spot failures early, maintain transparency, and control harmful or unexpected behaviors, you strengthen trust, reduce operational risk, and ensure your agents perform reliably across different environments.
In this module, you explore observability, MELT data, performance metrics, guardrails, and responsible AI principles. You learn how to monitor agent decisions, apply safety layers, evaluate behavior ethically, manage governance, and analyze real-world failures. You also dive into peer-sharing practices, logs, traces, escalation patterns, and structured review methods that help you refine, audit, and improve your agents continuously.
Module 8: Capstone Project – Design Your Own Intelligent Agent
Designing a complete AI agent from scratch gives you the chance to turn everything you’ve learned into a real, functional solution. This final stage pushes you to think creatively, solve practical problems, and build something that proves your ability to apply AI in real-world scenarios. As AI tools continue to expand across industries, you strengthen your ability to design agents that deliver value, automate tasks, and showcase your capability to move from theory to execution.
In this module, you work on a capstone project where you choose a use case and build an end-to-end intelligent agent using platforms like Relevance AI, Flowise, Langflow, Zapier, and n8n. You explore planning, development, testing, deployment, documentation, and presentation. You also dive into multiple sample agent workflows—such as personal assistants, sales agents, HR bots, and triage systems—while completing practical steps to design, validate, and deliver your own AI-powered solution.