AI+ Agent Specialty™
- Price 109 EUR + VAT
- E-learning Start any time
- Duration 8 hours of content, self-paced
- Language English
- Topic AI Specialization
How you can take it
- E-learning Start any time · 109 EUR + VAT Order
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Overview
What the course covers
The course, the materials and the exam are in English. The description below is the original AI CERTs® text.
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
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.
Audience
Who is it for
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.
In the price
What the price includes
- Self-paced online course with the full learning material
- The official AI CERTs® exam
- Digital badge after passing the exam
Course content
Syllabus
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Exam
About the exam
- 50 Questions
- 90 min Time limit
- 70% Pass mark
- Online proctored exam
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