Course Overview
TOPThe 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
TOPWhat You'll Learn
TOP- 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
TOPIntroduction 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
TOPRequired
- 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