Recommended Prerequisites:
- 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.
Course Outline:
Lesson 1: Introduction to AI Agents
- 1.1 Understanding AI Agents
- 1.2 Anatomy and Ecosystem of AI Agents
- 1.3 Applications, Misconceptions, and Mini Case Studies
- 1.4 Case Study: Transforming Customer Support at Acme Retail with AI Agents
- 1.5 Hands-On Exercise 1: Build a Q&A ChatBot Using Gemini + Prompt + LLM Chain in Flowise Cloud
Lesson 2: Core Concepts & Types of AI Agents
- 2.1 Anatomy of an AI Agent
- 2.2 Classification of AI Agents
- 2.3 Matching Agents to Use Cases
- 2.4 Case Study: Enhancing Mental Health Support with AI Agents at Earkick
- 2.5 Hands-On Exercise
Lesson 3: Tools for Non-Coders
- 3.1 No-code and visual agent platforms
- 3.2 Tools Overview and Setup
- 3.3 Start building: “Your First Flow” with n8n
- 3.4 Case Study: Empowering HR with AI – Building an Onboarding Assistant Without Coding
- 3.5 Hands-on Exercise
Lesson 4: Building Simple Agents
- 4.1 Agent 1
- 4.2 Agent 2
- 4.3 Agent 3
- 4.4 Agent 4
- 4.5 Troubleshooting and Validation of AI Agents
- 4.6 Share Your AI Agent
- 4.7 Hands-On Exercise 1
Lesson 5: Multi-Tool Agents and Workflow Automation
- 5.1 Multi-Tool Agents
- 5.2 Agent Chaining and Workflow Basics
- 5.3 Managing Agent State: State, Context, and User Journey
- 5.4 Prompt Engineering for Agents
- 5.5 Multi-Agent Systems (MAS)
- 5.6 Case Study: Smarter Marketing Campaigns with Tool Chaining
- 5.7 Hands-on Exercise: Automating Order Tracking and Notifications with Make.com
Lesson 6: Integration, Application Mapping & Deployment
- 6.1 Deploying Agents
- 6.2 Channel Selection – Where the User will Interact
- 6.3 Hosting Environment – Where does the Agent Run?
- 6.4 Data Integration
- 6.5 Security Setup
- 6.6 Monitoring & Updates
- 6.7 Application Mapping
- 6.8 Hands-on Exercise 1: Integration of a Portfolio Assistant Chatbot into GitHub Pages using Zapier
Lesson 7: Monitoring, Guardrails & Responsible AI
- 7.1 Observability Basics
- 7.2 Performance Evaluation: Key Metrics
- 7.3 Guardrails: Preventing Misuse & Ensuring Safe Outputs
- 7.4 Responsible AI
- 7.5 Mini-Case: Failure and Recovery in Agent Deployments
- 7.6 Real-world Failures
- 7.7 Peer Sharing: How to Present and Discuss Agent Logs/Results
Lesson 8: Capstone Project – Design Your Own Intelligent Agent
- 8.1 Capstone Project 1: Smart Personal AI Assistant
- 8.2 Capstone Project 2: Smart Lead Engagement – From Email to Personalized Outreach – Sales Support Agent
- 8.3 Capstone Project 3: Education Tutor Agent
- 8.4 HR Knowledge Bot
- 8.5 Customer Service Agent
- 8.6 Healthcare Triage Bot
