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
Why This Certification Matters
At a Glance: Course + Exam Overview
- Instructor-Led: 1 day (live or virtual)
- Self-Paced: 8 hours of content
Job Roles & Industry Outlook
User Experience Engineer
Design and build engaging, intuitive, and responsive digital interfaces that bring ideas to life and enhance user journeys.
AI Systems Engineer
Design and optimize data pipelines, warehouses, and systems to enable AI-driven analytics and applications.
Data Science & AI Specialist
Turn complex datasets into actionable insights by applying AI and machine learning models to solve business challenges.
Machine Learning Scientist
Design, build, and deploy machine learning models that power AI applications and deliver real-world business solutions.
Human Resources Specialist
Use AI to streamline recruitment, enhance employee engagement, and optimize workforce management strategies.
Cyber Security Analyst
Protect digital assets by identifying vulnerabilities, monitoring threats, and applying AI to strengthen security defenses.
Industry Growth: AI+ Agent™
- 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.
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.
What You'll Learn
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
Tools You'll Explore
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
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 Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via AI proctored exam platform (flexible scheduling)
Exam Blueprint
- Module 1: Introduction to AI Agents - 12%
- Module 2: Core Concepts & Types of AI Agents - 12%
- Module 3: Tools for Non-Coders - 12%
- Module 4: Building Simple Agents - 12%
- Module 5: Multi-Tool Agents and Workflow Automation - 13%
- Module 6: Integration, Application Mapping & Deployment - 13%
- Module 7: Monitoring, Guardrails & Responsible AI - 13%
- Module 8: Capstone Project – Design Your Own Intelligent Agent - 13%
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
- Access for Tablet & Phone
Frequently Asked Questions
The course includes a mix of theoretical knowledge and practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.
This course is ideal for developers, IT professionals, and anyone with a foundational understanding of AI and cloud computing who wants to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.
Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.
This certification enhances your professional profile by demonstrating proficiency in integrating AI with cloud computing. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities.
The certification includes an interactive capstone project where participants apply their knowledge to design and implement AI solutions within cloud environments. This project is designed to simulate real-world scenarios and challenges.