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AI+ Agent Specialty™
's-Hertogenbosch
ma 30 nov. 2026
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
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 Tools you will 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
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.
Instructor-led + Official exam + Digital badge
€895
Klassikaal
max 12
1 dag
AI+ Agent Specialty™ eLearning
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
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 Tools you will 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
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.
Instructor-led + Official exam + Digital badge
€200
E-Learning
max 999
1 dag
AI+ Pharma Practitioner™
Nieuwegein
wo 16 sep. 2026
en 1 andere data
Formerly known as AI+ Pharma™
Harness AI in Pharma to speed drug discovery, optimize trials, and enable precision therapies.
Revolutionize Healthcare Expertise with AI+ Pharma Practitioner™ for Smarter, Data-Driven Decisions
* Beginner-Friendly Pathway: Ideal for learners and professionals entering the world of AI in pharmaceuticals, offering clear fundamentals and easy-to-grasp concepts
* Integrated Learning Experience: Combines core pharma knowledge with intuitive AI tools, real-world case studies, and guided practice to strengthen analytical and operational skills
* Industry-Focused Growth: Equips you with practical projects, scenario-based exercises, and actionable insights to help you apply AI in drug development, research, compliance, and patient-centric solutions
Module 1: AI Foundations for Pharma
* 1.1 AI and Machine Learning Basics
* 1.2 AI Algorithms and Models
* 1.3 Use Case: Predictive Modeling for Adverse Drug Reactions and Drug-Drug Interactions Using Historical Patient Datasets
* 1.4 Hands-on: Build Predictive Models Using No-Code Tool (Teachable Machine) Module 2: AI in Drug Discovery and Development
* 2.1 AI in Molecular Drug Design
* 2.2 AI in Drug Repurposing
* 2.3 Use Case: AI-Driven Drug Repurposing Successes (COVID-19 Therapeutics)
* 2.4 Hands-On: Practical AI-Driven Molecular Design and Drug Repurposing Using Orange Data Mining Tool
* 2.5 Hands-On 2: Exploring Disease-Drug Associations with EpiGraphDB Module 3: Clinical Trials Optimization with AI
* 3.1 AI-Enhanced Patient Recruitment
* 3.2 Clinical Data Management and Monitoring
* 3.3 Use Case: Pfizer’s AI-Driven Analytics for Optimizing Clinical Trials
* 3.4 Hands-on: Implementing Clinical Data Analytics Using No-Code Platforms (KNIME) Module 4: Precision Medicine and Genomics
* 4.1 Personalized Treatment Strategies
* 4.2 Biomarker Discovery
* 4.3 Case Study: AI-Assisted Biomarker Discovery and Validation in Cancer Treatments
* 4.4 Hands-on: Hands-On Genomic Analysis – Exploring AI-Driven Genomic Interpretation Using CBioPortal Module 5: Regulatory and Ethical AI in Pharma
* 5.1 Ethical Considerations and AI Governance
* 5.2 AI Compliance and Regulatory Frameworks
* 5.3 Case Study: Analyzing Ethical and Regulatory Challenges Encountered in Major AI-Driven Pharma Initiatives
* 5.4 Hands-on: Developing AI Governance Strategies Based on Ethical Frameworks
* 5.5 Hands-on: Literature Mining with LitVar 2.0 Module 6: Implementing AI in Pharma Projects
* 6.1 AI Project Management
* 6.2 Evaluating AI Tools and ROI
* 6.3 Hands-On: Practical AI Project Management Using Airtable for Tracking, Collaboration, and Management Module 7: Future Trends and Sustainability in Pharma AI
* 7.1 Emerging AI Technologies in Pharma
* 7.2 AI for Sustainable Healthcare
* 7.3 Case Study: Analysis of Sustainability Initiatives Driven by AI in Pharmaceutical Industry Leaders
* 7.4 Hands-on: Scenario Planning and Predictive Analytics Using Dashboards for Future-Focused Decision Making Module 8: Capstone Project
* 8.1 Capstone Project 1: Predictive Modeling for Adverse Drug Reactions in Polypharmacy
* 8.2 Capstone Project 2: AI-Enhanced Clinical Trial Recruitment and Retention
* 8.3 Capstone Project 3: AI-Powered Drug Design for Rare Diseases
* 8.4 Capstone Project Evaluation Scheme Tools you will explore
* Python
* TensorFlow
* PyTorch
* Scikit-learn
* Pandas
* NumPy
* SQL
* Jupyter Notebooks
* MLflow
* DataBricks
* RDKit
* DeepChem
* Biopython
* Hugging Face Transformers for Biomedical NLP
* spaCy / Clinical NLP Toolkits
* Apache Spark for Healthcare Data
* Power BI / Tableau for Clinical Dashboards
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€895
Klassikaal
max 12
1 dag
AI+ Pharma Practitioner™ eLearning
Formerly known as AI+ Pharma™
Harness AI in Pharma to speed drug discovery, optimize trials, and enable precision therapies.
Revolutionize Healthcare Expertise with AI+ Pharma Practitioner™ for Smarter, Data-Driven Decisions
* Beginner-Friendly Pathway: Ideal for learners and professionals entering the world of AI in pharmaceuticals, offering clear fundamentals and easy-to-grasp concepts
* Integrated Learning Experience: Combines core pharma knowledge with intuitive AI tools, real-world case studies, and guided practice to strengthen analytical and operational skills
* Industry-Focused Growth: Equips you with practical projects, scenario-based exercises, and actionable insights to help you apply AI in drug development, research, compliance, and patient-centric solutions
Module 1: AI Foundations for Pharma
* 1.1 AI and Machine Learning Basics
* 1.2 AI Algorithms and Models
* 1.3 Use Case: Predictive Modeling for Adverse Drug Reactions and Drug-Drug Interactions Using Historical Patient Datasets
* 1.4 Hands-on: Build Predictive Models Using No-Code Tool (Teachable Machine) Module 2: AI in Drug Discovery and Development
* 2.1 AI in Molecular Drug Design
* 2.2 AI in Drug Repurposing
* 2.3 Use Case: AI-Driven Drug Repurposing Successes (COVID-19 Therapeutics)
* 2.4 Hands-On: Practical AI-Driven Molecular Design and Drug Repurposing Using Orange Data Mining Tool
* 2.5 Hands-On 2: Exploring Disease-Drug Associations with EpiGraphDB Module 3: Clinical Trials Optimization with AI
* 3.1 AI-Enhanced Patient Recruitment
* 3.2 Clinical Data Management and Monitoring
* 3.3 Use Case: Pfizer’s AI-Driven Analytics for Optimizing Clinical Trials
* 3.4 Hands-on: Implementing Clinical Data Analytics Using No-Code Platforms (KNIME) Module 4: Precision Medicine and Genomics
* 4.1 Personalized Treatment Strategies
* 4.2 Biomarker Discovery
* 4.3 Case Study: AI-Assisted Biomarker Discovery and Validation in Cancer Treatments
* 4.4 Hands-on: Hands-On Genomic Analysis – Exploring AI-Driven Genomic Interpretation Using CBioPortal Module 5: Regulatory and Ethical AI in Pharma
* 5.1 Ethical Considerations and AI Governance
* 5.2 AI Compliance and Regulatory Frameworks
* 5.3 Case Study: Analyzing Ethical and Regulatory Challenges Encountered in Major AI-Driven Pharma Initiatives
* 5.4 Hands-on: Developing AI Governance Strategies Based on Ethical Frameworks
* 5.5 Hands-on: Literature Mining with LitVar 2.0 Module 6: Implementing AI in Pharma Projects
* 6.1 AI Project Management
* 6.2 Evaluating AI Tools and ROI
* 6.3 Hands-On: Practical AI Project Management Using Airtable for Tracking, Collaboration, and Management Module 7: Future Trends and Sustainability in Pharma AI
* 7.1 Emerging AI Technologies in Pharma
* 7.2 AI for Sustainable Healthcare
* 7.3 Case Study: Analysis of Sustainability Initiatives Driven by AI in Pharmaceutical Industry Leaders
* 7.4 Hands-on: Scenario Planning and Predictive Analytics Using Dashboards for Future-Focused Decision Making Module 8: Capstone Project
* 8.1 Capstone Project 1: Predictive Modeling for Adverse Drug Reactions in Polypharmacy
* 8.2 Capstone Project 2: AI-Enhanced Clinical Trial Recruitment and Retention
* 8.3 Capstone Project 3: AI-Powered Drug Design for Rare Diseases
* 8.4 Capstone Project Evaluation Scheme Tools you will explore
* Python
* TensorFlow
* PyTorch
* Scikit-learn
* Pandas
* NumPy
* SQL
* Jupyter Notebooks
* MLflow
* DataBricks
* RDKit
* DeepChem
* Biopython
* Hugging Face Transformers for Biomedical NLP
* spaCy / Clinical NLP Toolkits
* Apache Spark for Healthcare Data
* Power BI / Tableau for Clinical Dashboards
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€200
E-Learning
max 999
1 dag
AI+ Mining Practitioner™
Formerly known as AI+ Mining™
Unlock the potential of AI in Mining to optimize exploration, improve resource management, and automate operations.
* Powering the Next Era of Mining with AI: Smarter, Safer, and Sustainable Operations
* Beginner-Friendly Course: Perfect introduction to explore how AI transforms modern mining practices
* Foundational Learning: Explains AI-driven exploration, automation, data analysis, and safety innovations
* No Technical Background Needed: Open to anyone eager to understand the role of technology in mining
Module 1: Introduction to AI in Mining
* 1.1 Overview of AI, ML & Deep Learning in Mining
* 1.2 Use Cases
* 1.3 Activity Module 2: Machine Learning & Deep Learning for Mining
* 2.1 Introduction to ML & Deep Learning
* 2.2 Use Cases
* 2.3 Case Study
* 2.4 Hands-On Exercise
* 2.5 Activity Module 3: AI in Mineral Exploration & Resource Modeling
* 3.1 AI for Smart Exploration & Orebody Modeling
* 3.2 Use-Cases
* 3.3 Case Study
* 3.4 Hands-on Exercises
* 3.5 Activity Module 4: AI for Equipment Automation & Fleet Optimization
* 4.1 AI in Autonomous Vehicles & Robotics
* 4.2 Use Cases
* 4.3 Case Study
* 4.4 Hands-On Exercise
* 4.5 Activity Module 5: AI in Predictive Maintenance & Asset Management
* 5.1 AI in Equipment Health Monitoring
* 5.2 Use Cases
* 5.3 Case Study
* 5.4 Hands-On Exercise
* 5.5 Activity Module 6: AI for Environmental Compliance & Sustainability
* 6.1 AI-Powered Environmental Monitoring
* 6.2 Use Cases
* 6.3 Case Study
* 6.4 Hands-On Exercises
* 6.5 Activity: Group Exercise Module 7: AI for Workforce Transformation & Ethical AI
* 7.1 Ethical AI, Workforce Augmentation & AI Regulations
* 7.2 Use Cases
* 7.3 Case Study
* 7.4 Hands-On Exercises Module 8: AI in Mining Strategy & Implementation
* 8.1 AI-Driven Decision-Making in Mining
* 8.2 Use Cases
* 8.3 Case Study Tools you will explore
* TensorFlow
* Keras
* Hadoop
* Python
* Tableau
* Matplotlib
* SQL
* Apache Spark
* Predictive Maintenance Software
* Mining Simulation Tools
* Computer Vision Tools
* IoT Integration Platforms
* Accela Civic Platform
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€895
Klassikaal
max 12
1 dag
AI+ Mining Practitioner™ eLearning
Formerly known as AI+ Mining™
Unlock the potential of AI in Mining to optimize exploration, improve resource management, and automate operations.
* Powering the Next Era of Mining with AI: Smarter, Safer, and Sustainable Operations
* Beginner-Friendly Course: Perfect introduction to explore how AI transforms modern mining practices
* Foundational Learning: Explains AI-driven exploration, automation, data analysis, and safety innovations
* No Technical Background Needed: Open to anyone eager to understand the role of technology in mining
Module 1: Introduction to AI in Mining
* 1.1 Overview of AI, ML & Deep Learning in Mining
* 1.2 Use Cases
* 1.3 Activity Module 2: Machine Learning & Deep Learning for Mining
* 2.1 Introduction to ML & Deep Learning
* 2.2 Use Cases
* 2.3 Case Study
* 2.4 Hands-On Exercise
* 2.5 Activity Module 3: AI in Mineral Exploration & Resource Modeling
* 3.1 AI for Smart Exploration & Orebody Modeling
* 3.2 Use-Cases
* 3.3 Case Study
* 3.4 Hands-on Exercises
* 3.5 Activity Module 4: AI for Equipment Automation & Fleet Optimization
* 4.1 AI in Autonomous Vehicles & Robotics
* 4.2 Use Cases
* 4.3 Case Study
* 4.4 Hands-On Exercise
* 4.5 Activity Module 5: AI in Predictive Maintenance & Asset Management
* 5.1 AI in Equipment Health Monitoring
* 5.2 Use Cases
* 5.3 Case Study
* 5.4 Hands-On Exercise
* 5.5 Activity Module 6: AI for Environmental Compliance & Sustainability
* 6.1 AI-Powered Environmental Monitoring
* 6.2 Use Cases
* 6.3 Case Study
* 6.4 Hands-On Exercises
* 6.5 Activity: Group Exercise Module 7: AI for Workforce Transformation & Ethical AI
* 7.1 Ethical AI, Workforce Augmentation & AI Regulations
* 7.2 Use Cases
* 7.3 Case Study
* 7.4 Hands-On Exercises Module 8: AI in Mining Strategy & Implementation
* 8.1 AI-Driven Decision-Making in Mining
* 8.2 Use Cases
* 8.3 Case Study Tools you will explore
* TensorFlow
* Keras
* Hadoop
* Python
* Tableau
* Matplotlib
* SQL
* Apache Spark
* Predictive Maintenance Software
* Mining Simulation Tools
* Computer Vision Tools
* IoT Integration Platforms
* Accela Civic Platform
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€200
E-Learning
max 999
1 dag
AI+ Customer Service Practitioner™
Formerly known as AI+ Customer Service™
Enhance Customer Experiences: Employ AI-Powered Service Solutions
* Customer-Centric AI: Redefine service workflows with AI-powered personalization
* Practical Execution: Implement automation tools to optimize CX and satisfaction
* Ethical AI Integration: Covers trust-building and responsible AI practices
* Competitive Edge: Learn to enhance communication and service delivery at scale
Course Overview
* Course Introduction Preview Module 1: Introduction to Artificial Intelligence (AI) in Customer Service
* 1.1 Overview of AI
* 1.2 Relevance of AI in Customer Service Module 2: Understanding AI Technologies
* 2.1 Overview of Machine Learning
* 2.2 Natural Language Processing (NLP)
* 2.3 Deep Learning and Neural Networks
* 2.4 AI-Driven Analytics Module 3: Data Collection and Analysis
* 3.1 Gathering Customer Data
* 3.2 Data Quality and Integrity
* 3.3 Analyzing Data for Insights
* 3.4 Applying Insights to Enhance Customer Service Module 4: Implementing AI Solutions
* 4.1 AI Solutions for Customer Service
* 4.2 Integration into Customer Service Systems
* 4.3 Training and Change Management
* 4.4 Measuring the Impact of AI on Customer Service Module 5: Optimizing Customer Experiences
* 5.1 Using AI to Create Personalized Customer Interactions
* 5.2 Increasing Service Efficiency with AI
* 5.3 Case Studies: Successful AI Implementations in Customer Service Module 6: Ethical Considerations and Trust
* 6.1 Ethical AI Use in Customer Service
* 6.2 Building Trust through Transparency
* 6.3 Compliance with Data Privacy Regulations Module 7: Future of AI in Customer Service
* 7.1 Emerging Trends and Advancements in AI Technologies
* 7.2 Innovative Use Cases for AI in Customer Service
* 7.3 Preparing for AI Evolution in Customer Service
* 7.4 Ethical and Societal Considerations Module 8: Creating an AI Strategy for Your Organization
* 8.1 Developing Strategic Plan for AI Implementation and Evolution
* 8.2 Cultivating an AI-Driven Culture
* 8.3 Overcoming Challenges and Measuring Success Optional Module: AI Agents for Customer Service
* 1. What Are AI Agents
* 2. Types of AI Agents
* 3. Applications and Trends of AI Agents in Customer Service Tools you will explore
* Zendesk
* Freddy AI
* Octane AI
* Rul.ai
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€895
Klassikaal
max 12
1 dag
AI+ Customer Service Practitioner™ eLearning
Formerly known as AI+ Customer Service™
Enhance Customer Experiences: Employ AI-Powered Service Solutions
* Customer-Centric AI: Redefine service workflows with AI-powered personalization
* Practical Execution: Implement automation tools to optimize CX and satisfaction
* Ethical AI Integration: Covers trust-building and responsible AI practices
* Competitive Edge: Learn to enhance communication and service delivery at scale
Course Overview
* Course Introduction Preview Module 1: Introduction to Artificial Intelligence (AI) in Customer Service
* 1.1 Overview of AI
* 1.2 Relevance of AI in Customer Service Module 2: Understanding AI Technologies
* 2.1 Overview of Machine Learning
* 2.2 Natural Language Processing (NLP)
* 2.3 Deep Learning and Neural Networks
* 2.4 AI-Driven Analytics Module 3: Data Collection and Analysis
* 3.1 Gathering Customer Data
* 3.2 Data Quality and Integrity
* 3.3 Analyzing Data for Insights
* 3.4 Applying Insights to Enhance Customer Service Module 4: Implementing AI Solutions
* 4.1 AI Solutions for Customer Service
* 4.2 Integration into Customer Service Systems
* 4.3 Training and Change Management
* 4.4 Measuring the Impact of AI on Customer Service Module 5: Optimizing Customer Experiences
* 5.1 Using AI to Create Personalized Customer Interactions
* 5.2 Increasing Service Efficiency with AI
* 5.3 Case Studies: Successful AI Implementations in Customer Service Module 6: Ethical Considerations and Trust
* 6.1 Ethical AI Use in Customer Service
* 6.2 Building Trust through Transparency
* 6.3 Compliance with Data Privacy Regulations Module 7: Future of AI in Customer Service
* 7.1 Emerging Trends and Advancements in AI Technologies
* 7.2 Innovative Use Cases for AI in Customer Service
* 7.3 Preparing for AI Evolution in Customer Service
* 7.4 Ethical and Societal Considerations Module 8: Creating an AI Strategy for Your Organization
* 8.1 Developing Strategic Plan for AI Implementation and Evolution
* 8.2 Cultivating an AI-Driven Culture
* 8.3 Overcoming Challenges and Measuring Success Optional Module: AI Agents for Customer Service
* 1. What Are AI Agents
* 2. Types of AI Agents
* 3. Applications and Trends of AI Agents in Customer Service Tools you will explore
* Zendesk
* Freddy AI
* Octane AI
* Rul.ai
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€200
E-Learning
max 999
1 dag
AI+ Finance Practitioner™
Formerly known as AI+ Finance™
Maximize Returns with AI-Enhanced Financial Strategies
* Finance Transformation: Explore AI use in credit risk, fraud detection, and forecasting
* Smart Modelling: Apply predictive analytics and blockchain in financial strategies
* Practical AI Tools: Optimize operations and decision-making with hands-on training
* Strategic Readiness: Build financial resilience in complex economic ecosystems
Course Overview
* Course Introduction Preview Module 1: Introduction to Artificial Intelligence (AI) and Its Impact on Finance
* 1.1 Fundamentals of AI in Finance
* 1.2 Data-Driven Decision Making in Finance
* 1.3 AI Technologies Shaping the Financial Landscape Module 2: Data-Driven Decision Making in Finance
* 2.1 The Power of Financial Data
* 2.2 Analytics and Insights in Finance
* 2.3 Implementing AI for Strategic Financial Decision-Making Module 3: Enhancing Credit and Loans with AI
* 3.1 Revolutionizing Credit Scoring with AI
* 3.2 Automating Loan Origination and Processing
* 3.3 Personalization and Customer Experience in Lending Module 4: Fraud Detection in Finance with AI
* 4.1 The Landscape of Financial Fraud
* 4.2 AI and Machine Learning in Fraud Detection
* 4.3 Future Directions in AI-driven Fraud Detection Module 5: Forecasting Stock Market with AI
* 5.1 Overview of Stock Market Analysis
* 5.2 AI Technologies in Stock Forecasting
* 5.3 Challenges and Future of AI in Stock Market Forecasting Module 6: Blockchain and AI: Revolutionizing Finance
* 6.1 Introduction to Blockchain in Finance
* 6.2 Synergy of AI and Blockchain in Finance
* 6.3 Future Perspectives and Ethical Considerations Module 7: Emerging Technologies and Their Impact on Finance
* 7.1 The Expanding Universe of FinTech
* 7.2 Next-Generation Technologies Shaping Finance
* 7.3 Integrating Emerging Technologies into Financial Services Module 8: Implementing AI Strategies in Finance
* 8.1 Building a Digital-First Finance Strategy
* 8.2 Operationalizing AI and Emerging Technologies
* 8.3 Looking Ahead: The Future of Financial Services Optional Module: AI Agents for Finance
* 1. What Are AI Agents for Finance
* 2. Types of AI Agents in Finance
* 3. Significance of AI Agents in Finance Tools you will explore
* Sentieo
* Magnifi
* QuantConnect
* AlphaSense
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€895
Klassikaal
max 12
1 dag
AI+ Finance Practitioner™ eLearning
Formerly known as AI+ Finance™
Maximize Returns with AI-Enhanced Financial Strategies
* Finance Transformation: Explore AI use in credit risk, fraud detection, and forecasting
* Smart Modelling: Apply predictive analytics and blockchain in financial strategies
* Practical AI Tools: Optimize operations and decision-making with hands-on training
* Strategic Readiness: Build financial resilience in complex economic ecosystems
Course Overview
* Course Introduction Preview Module 1: Introduction to Artificial Intelligence (AI) and Its Impact on Finance
* 1.1 Fundamentals of AI in Finance
* 1.2 Data-Driven Decision Making in Finance
* 1.3 AI Technologies Shaping the Financial Landscape Module 2: Data-Driven Decision Making in Finance
* 2.1 The Power of Financial Data
* 2.2 Analytics and Insights in Finance
* 2.3 Implementing AI for Strategic Financial Decision-Making Module 3: Enhancing Credit and Loans with AI
* 3.1 Revolutionizing Credit Scoring with AI
* 3.2 Automating Loan Origination and Processing
* 3.3 Personalization and Customer Experience in Lending Module 4: Fraud Detection in Finance with AI
* 4.1 The Landscape of Financial Fraud
* 4.2 AI and Machine Learning in Fraud Detection
* 4.3 Future Directions in AI-driven Fraud Detection Module 5: Forecasting Stock Market with AI
* 5.1 Overview of Stock Market Analysis
* 5.2 AI Technologies in Stock Forecasting
* 5.3 Challenges and Future of AI in Stock Market Forecasting Module 6: Blockchain and AI: Revolutionizing Finance
* 6.1 Introduction to Blockchain in Finance
* 6.2 Synergy of AI and Blockchain in Finance
* 6.3 Future Perspectives and Ethical Considerations Module 7: Emerging Technologies and Their Impact on Finance
* 7.1 The Expanding Universe of FinTech
* 7.2 Next-Generation Technologies Shaping Finance
* 7.3 Integrating Emerging Technologies into Financial Services Module 8: Implementing AI Strategies in Finance
* 8.1 Building a Digital-First Finance Strategy
* 8.2 Operationalizing AI and Emerging Technologies
* 8.3 Looking Ahead: The Future of Financial Services Optional Module: AI Agents for Finance
* 1. What Are AI Agents for Finance
* 2. Types of AI Agents in Finance
* 3. Significance of AI Agents in Finance Tools you will explore
* Sentieo
* Magnifi
* QuantConnect
* AlphaSense
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.
Instructor-led OR Self-paced course + Official exam + Digital badge
€200
E-Learning
max 999
1 dag