Opleiding: AI+ Agent Specialty™

Formerly known as AI+ Agent™

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

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

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.

• 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.

• 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

• 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

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

De OCICT maatwerk-methode houdt in dat op basis van de behoefte van de klant - en indien nodig na een intakegesprek - een individueel opleidingstraject wordt opgesteld. De trainingen worden veelal individueel gevolgd, zodat iedere training een maatwerktraject is. Klassikale trainingen zijn natuurlijk mogelijk, mits ze aansluiten bij de leerbehoeften van de deelnemers / opdrachtgever.

Alle onderdelen van de training kennen een voortdurende wisselwerking tussen theorie en praktijk. De inhoud van de training kan vooraf per cursist worden aangepast en tijdens de cursus worden bijgesteld. De focus ligt op maatwerk: het traject wordt afgestemd op de doelstellingen van de deelnemer(s) en/of opdrachtgever, ongeacht of het individueel of klassikaal wordt aangeboden.