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AI+ Agent Specialty™

AI+ Agent Specialty™

Empower Automation with AI+ Agent Specialty™ 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
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Certificate Code

AP 1401

Exam Format

AI-Driven Remote Exam Proctoring

Course Overview

Important details and certification information

Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
Basic understanding of AI concepts, programming knowledge in Python or similar languages, and foundational data analysis skills. Perfect for learners with a problem-solving mindset who want to apply analytical thinking to real-world AI challenges and intelligent agent development.
50 questions, 70% passing, 90 minutes, online proctored exam

Certification Modules

  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

  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

  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

  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

  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

  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

  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

  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

AI Tools Covered

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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