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AI+ Agent™

AP 1401

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
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Why This Certification Matters

Industry Recognition: A specialized credential that signals strong capability in AI agent design, deployment, and management.
Career Differentiation: A standout addition to your profile that highlights expertise in AI-powered automation and intelligent workflows.
Hands-on Proficiency: Demonstrated experience using agent-building tools, frameworks, and best practices to solve real problems.
Business Value Creation: Proven ability to build agents that streamline operations, elevate customer experiences, and drive measurable ROI.
Future-ready Skill Set: Strong alignment with the growing demand for AI agents across industries, keeping your skills relevant and competitive.

At a Glance: Course + Exam Overview

Program Name 
AI+ Agent™
Included 
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration 
  • Instructor-Led: 1 day (live or virtual)
  • Self-Paced: 8 hours of content
Prerequisites
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.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
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Who Should Enroll?

  • Aspiring AI Professionals: Learners looking to break into AI by building practical experience with intelligent agents and automation.

  • Software Developers & Engineers: Python or similar language programmers who want to design, integrate, and deploy AI agents into real applications.

  • Data Analysts & Data Scientists: Professionals who work with data and want to operationalize insights through AI-driven agents and workflows.

  • Product Managers & Tech Leaders: Decision-makers aiming to understand, plan, and oversee AI agent solutions that enhance products and services.

  • Automation & Operations Specialists: Those focused on process optimization who want to replace repetitive tasks with smart, autonomous AI agents.

Job Roles & Industry Outlook 

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AI Agent Solutions Architect:

Design and implement end-to-end AI agent ecosystems that automate complex workflows and integrate seamlessly with enterprise systems.

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Conversational & Virtual Agent Designer:

Create intelligent customer-facing agents that handle inquiries, personalize interactions, and enhance user experiences across digital channels.

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utomation & Operations Lead:

Oversee deployment, monitoring, and optimization of AI agents to ensure reliability, scalability, and continuous improvement in automated processes.

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AI Agent Product Manager:

Define strategy, roadmap, and performance metrics for agent-based products and platforms that drive business value and innovation.

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Head of Intelligent Agent Transformation:

Lead organization-wide adoption of AI agents, aligning technology, teams, and processes to enable scalable, autonomous operations.

Skills You’ll Gain

  • AI Agent Architecture & Design
  • Conversational & Task-Oriented Agent Building
  • Multi-Agent System Orchestration
  • Tool & API Integration
  • Intelligent Workflow Automation
  • Context Management & Prompt Engineering
  • Agent Monitoring & Optimization
  • Human-in-the-Loop Supervision
  • Responsible & Trustworthy Agent Deployment

What You'll Learn

  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

Tools You'll Explore

Tool Python

Python

Tool LangChain

LangChain

Tool LlamaIndex

LlamaIndex

Tool OpenAI API

OpenAI API

Tool Hugging Face Inference

Hugging Face Inference

Tool Multi-Agent Orchestration Frameworks

Multi-Agent Orchestration Frameworks

Tool Vector Databases (e.g., Pinecone, Chroma)

Vector Databases (e.g., Pinecone, Chroma)

Tool Workflow Orchestration (e.g., Airflow, Prefect)

Workflow Orchestration (e.g., Airflow, Prefect)

Tool Jupyter Notebooks

Jupyter Notebooks

Tool Docker

Docker

Tool Prompt Engineering Platforms

Prompt Engineering Platforms

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.

Exam Details

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Delivery Method

Online via proctored exam platform (flexible scheduling)

Exam Blueprint

  • Introduction to AI Agents – 7%
  • Core Concepts and Types of AI Agents – 15%
  • Tools for Non-Coders – 15%
  • Building Simple Agents – 15%
  • AI Agent Builder – 12%
  • Integration, Application Mapping & Deployment – 12%
  • Monitoring, Guardrails & Responsible AI – 12%
  • Capstone Project – Design Your Own Intelligent Agent – 12%

Choose the Format That Fits Your Schedule

What’s Included (One-Year Subscription + All Updates):

  • High-Quality Videos, E-book (PDF & Audio), and Podcasts
  • AI Mentor for Personalized Guidance
  • Quizzes, Assessments, and Course Resources
  • Online Proctored Exam with One Free Retake
  • Comprehensive Exam Study Guide

Instructor-Led (Live Virtual/Classroom)

  • 1 day of intensive training with live demos
  • Real-time Q&A, peer collaboration, and hands-on labs
  • Led by AI Certified Trainers and delivered through Authorized Training Partners
Purchase Instructor-Led Course

Self-Paced Online

  • ~8 hours of on-demand video lessons, e-book, podcasts, and interactive labs
  • Learn anywhere, anytime, with modular quizzes to track progress
Purchase Self-Paced Course

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Frequently Asked Questions

Yes, this certification is highly practical, focusing on building and deploying AI agents for real workflows. You’ll be able to apply agent-based automation directly to business processes, customer journeys, and internal operations.

This certification focuses specifically on intelligent agent design, orchestration, and deployment—going beyond theory to show how agents can act, decide, and collaborate across tools, apps, and systems in real business environments.

You’ll build task-oriented and conversational agents, multi-agent workflows, tool-using agents, and process-automation solutions—mirroring real organizational use cases like support automation, internal copilots, and workflow agents.

The course combines expert-led lessons, guided labs, and project-based learning where you design, configure, and deploy agents end-to-end, ensuring you gain hands-on, implementation-ready skills—not just conceptual knowledge.

It equips you with in-demand skills in agent building, orchestration, and automation, along with a portfolio of agent projects that align with emerging roles in AI engineering, automation, and intelligent systems design.