AI+ Agent™

Empower businesses with AI + Agent ™ to design, deploy, and scale intelligent agents.

Empower Automation with AI+ Agent™ for intelligent, efficient task execution

  • Beginner-Friendly Pathway: Perfect for learners stepping into the world of AI agents, offering simple, structured guidance for confident skill-building
  • Immersive Learning Experience: Combines essential AI agent fundamentals, intuitive tools, and real-world workflows to help you understand, build, and deploy automated agents
  • Action-Oriented Skill Development: Features practical exercises, scenario-based tasks, and guided projects so you can design, optimise, and showcase high-performance AI agents with ease

Módulos

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

Herramientas de IA

  • Python
  • LangChain
  • LlamaIndex
  • OpenAI API
  • Hugging Face Inference
  • Multi-Agent Orchestration Frameworks
  • Vector Databases (e.g., Pinecone, Chroma)
  • Workflow Orchestration (e.g., Airflow, Prefect)
  • Jupyter Notebooks
  • Docker
  • Prompt Engineering Platforms
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