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AI+ Agent Specialty

SS Course: 9000605

Course Overview

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The AI+ Agent Specialty™ provides a practical, end-to-end understanding of how AI agents are designed, built, and deployed across modern workflows. This course breaks down the architecture behind autonomous, task-driven agents from prompt routing and tool integration to multi-agent collaboration and real-time decision-making. Learners explore agent behavior design, workflow orchestration, retrieval augmentation, and automation patterns used across industries. Through hands-on labs, they configure, test, and optimize AI agents capable of reasoning, planning, and executing tasks independently. It’s a foundational specialization for anyone building or integrating AI agents into business or technical environments.

                                                                  

Scheduled Classes

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07/22/26 - NVT - Virtual Classroom - Virtual-Instructor Led (click to enroll)
08/26/26 - NVT - Virtual Classroom - Virtual-Instructor Led (click to enroll)
09/23/26 - NVT - Virtual Classroom - Virtual-Instructor Led (click to enroll)
10/28/26 - NVT - Virtual Classroom - Virtual-Instructor Led (click to enroll)
11/25/26 - NVT - Virtual Classroom - Virtual-Instructor Led (click to enroll)
12/23/26 - NVT - Virtual Classroom - Virtual-Instructor Led (click to enroll)

What You'll Learn

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  • Understand agent architecture, components, and operational workflows
  • Learn how agents reason, plan, route prompts, and interact with tools/APIs
  • Build autonomous agents for tasks such as research, summarization, data retrieval, and automation
  • Apply RAG (Retrieval-Augmented Generation) to enhance agent accuracy and context awareness
  • Implement multi-agent systems with role-based collaboration and task delegation
  • Configure guardrails, monitoring, safety layers, and ethical compliance for agent deployments
  • Test, optimize, and evaluate agent outputs for reliability and performance

Outline

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Introduction to AI Agents

  • Understanding AI Agents
  • Anatomy and Ecosystem of AI Agents
  • Applications, Misconceptions, and Mini Case Studies
  • Case Study: Transforming Customer Support at Acme Retail with AI Agents
  • Hands-On Exercise 1: Build a Q&A ChatBot Using Gemini + Prompt + LLM Chain in Flowise Cloud

Core Concepts & Types of AI Agents

  • Anatomy of an AI Agent
  • Classification of AI Agents
  • Matching Agents to Use Cases
  • Case Study: Enhancing Mental Health Support with AI Agents at Earkick
  • Hands-On Exercise

Tools for Non-Coders

  • No-code and visual agent platforms
  • Tools Overview and Setup
  • Start building: “Your First Flow” with n8n
  • Case Study: Empowering HR with AI – Building an Onboarding Assistant Without Coding
  • Hands-on Exercise

Building Simple Agents

  • Agent 1
  • Agent 2
  • Agent 3
  • Agent 4
  • Troubleshooting and Validation of AI Agents
  • Share Your AI Agent
  • Hands-On Exercise 1

Multi-Tool Agents and Workflow Automation

  • Multi-Tool Agents
  • Agent Chaining and Workflow Basics
  • Managing Agent State: State, Context, and User Journey
  • Prompt Engineering for Agents
  • Multi-Agent Systems (MAS)
  • Case Study: Smarter Marketing Campaigns with Tool Chaining
  • Hands-on Exercise: Automating Order Tracking and Notifications with Make.com

Prerequisites

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Required

  • Basic Understanding of AI Concepts – Familiarity with core AI principles
  • Programming Knowledge – Proficiency in Python or similar languages
  • Data Analysis Skills – Ability to interpret and manipulate datasets
  • Problem-Solving Mindset – Analytical thinking to address AI challenges
  • Familiarity with Machine Learning – Understanding basic ML algorithms and techniques

    Who Should Attend

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    Next Step Courses

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