Opleidingen
68.955
resultaten
AutoGPT Workflow Automation
Amsterdam
ma 20 jul. 2026
en 9 andere data
The course AutoGPT Workflow Automation from SpiralTrain teaches you how to build autonomous AI agents using AutoGPT and similar frameworks.
Introduction AutoGPT
The course AutoGPT Workflow Automation begins with an introduction to autonomous AI agents and AutoGPT. Agent frameworks comparison, installation, configuration, goal setting, memory systems, and practical use cases are explored.
Agent Architecture
This module covers the agent loop design including goal decomposition, task planning, reasoning processes, self-reflection, critique mechanisms, decision making, action selection, and feedback loops for continuous improvement.
Tools and Plugins
Here participants learn to work with built-in tools and develop custom tools. Topics include API integrations, web browsing, file operations, code execution, search capabilities, database access, and plugin architecture.
Memory Management
Memory systems are addressed including short-term and long-term memory, vector databases, retrieval strategies, context window management, conversation history, knowledge storage, embeddings, and state persistence for autonomous agents.
Advanced Capabilities
This part focuses on advanced features including multi-agent systems, agent collaboration, human-in-the-loop workflows, constraint management, cost optimization, error handling, guardrails, safety mechanisms, and workflow orchestration.
Production Deployment
The course concludes with production considerations including deployment strategies, environment configuration, API management, monitoring, error recovery, scaling, security best practices, cost management, and testing autonomous agents.
Audience Course AutoGPT Workflow Automation
This course is intended for AI developers, automation engineers, and data scientists who want to build autonomous AI agents using AutoGPT.
Prerequisites Course AutoGPT Workflow Automation
Participants should have a good understanding of Python Programming en AI and LLM concepts. Familiarity with APIs and prompt engineering is beneficial.
Realization Training AutoGPT Workflow Automation
The training combines theoretical instruction with hands-on labs guided by a trainer. Participants build several autonomous agents throughout the course.
AutoGPT Workflow Automation Certificate
After successful completion, participants receive a certificate of participation in AutoGPT Workflow Automation.
Modules
Module 1: Introduction AutoGPT
AutoGPT Overview
Autonomous Agents Concepts
AutoGPT vs ChatGPT
Agent Frameworks Comparison
Installation and Setup
Configuration Basics
Agent Goals
Memory Systems
Use Cases
Best Practices
Module 2: Agent Architecture
Agent Loop Design
Goal Decomposition
Task Planning
Reasoning Processes
Self-Reflection Mechanisms
Critique and Refinement
Decision Making
Action Selection
Feedback Loops
Agent Personas
Module 3: Tools and Plugins
Built-in Tools
Custom Tool Development
API Integrations
Web Browsing
File Operations
Code Execution
Search Capabilities
Database Access
Tool Chaining
Plugin Architecture
Module 4: Memory Management
Short-Term Memory
Long-Term Memory
Vector Databases
Memory Retrieval
Context Window Management
Conversation History
Knowledge Storage
Embedding Strategies
Memory Optimization
State Persistence
Module 5: Advanced Capabilities
Multi-Agent Systems
Agent Collaboration
Human-in-the-Loop
Constraint Management
Cost Optimization
Error Handling
Guardrails Implementation
Safety Mechanisms
Performance Tuning
Workflow Orchestration
Module 6: Production Deployment
Deployment Strategies
Environment Configuration
API Key Management
Monitoring and Logging
Error Recovery
Scaling Considerations
Security Best Practices
Cost Management
Testing Autonomous Agents
Production Checklist
€1.699
Klassikaal
max 12
2 dagen
Azure AI
Amsterdam
vr 3 jul. 2026
en 9 andere data
The course Azure AI from SpiralTrain teaches you how to build and deploy intelligent applications using Microsoft Azure AI services.
Azure AI Platform
The course Azure AI begins with an overview of the Azure AI platform including service categories, portal navigation, resource management, authentication, API configuration, and pricing models for Azure AI services.
Cognitive Services
This module covers Azure Cognitive Services including vision services for image analysis, face recognition, custom vision, language services for text analytics, translation, speech processing, content moderation, and document intelligence capabilities.
Azure OpenAI
Here participants learn to work with Azure OpenAI Service including GPT models, ChatGPT integration, prompt engineering techniques, model fine-tuning, embeddings, responsible AI practices, content filtering, and token management strategies.
ML and Deployment
The course concludes with Azure Machine Learning fundamentals, ML Studio usage, model training and deployment, MLOps basics, monitoring solutions, security configuration, integration patterns, and production deployment best practices.
Audience Course Azure AI
This course is intended for developers, AI engineers, and cloud architects who want to build applications using Azure AI services.
Prerequisites Course Azure AI
Participants should have programming knowledge and familiarity with cloud concepts. Experience with Azure portal and REST APIs is beneficial.
Realization Training Azure AI
The training combines theoretical instruction with hands-on labs using Azure services guided by a trainer. Participants build several AI applications throughout the course.
Azure AI Certificate
After successful completion, participants receive a certificate of participation in Azure AI.
Modules
Module 1: Azure AI Platform
Azure AI Overview
AI Service Categories
Azure Portal Navigation
Resource Management
Service Tiers
Authentication Methods
API Keys
Endpoints Configuration
Pricing Models
Best Practices
Module 2: Cognitive Services
Vision Services
Computer Vision API
Face Recognition
Custom Vision
Language Services
Text Analytics
Translator Service
Speech Services
Content Moderation
Document Intelligence
Module 3: Azure OpenAI
Azure OpenAI Service
GPT Models
ChatGPT Integration
Prompt Engineering
Fine-Tuning Models
Embeddings
Responsible AI
Content Filtering
Token Management
Cost Optimization
Module 4: ML and Deployment
Azure Machine Learning
ML Studio
Model Training
Model Deployment
MLOps Basics
Monitoring Solutions
Security Configuration
Integration Patterns
Production Best Practices
Hands-On Projects
€799
Klassikaal
max 12
1 dag
AI for Managers
Amsterdam
vr 10 jul. 2026
en 9 andere data
The course AI Overview for Managers from SpiralTrain teaches you how to understand and leverage artificial intelligence for strategic business decisions.
AI Fundamentals
The course AI Overview for Managers begins with fundamental AI concepts including machine learning, deep learning, generative AI, and large language models. AI capabilities, limitations, and the current landscape are explored.
Business Applications
This module covers practical AI use cases across business functions including customer service, marketing, operations, and data analysis. Industry examples, competitive advantages, and ROI considerations are discussed.
Implementation Strategy
Here participants learn to develop AI implementation strategies including readiness assessment, data requirements, technology decisions, vendor selection, pilot projects, change management, team building, and defining success metrics.
Leadership and Governance
The course concludes with ethical considerations, responsible AI, privacy, compliance, risk management, governance frameworks, stakeholder communication, budget planning, and developing long-term AI strategies with actionable plans.
Audience Course AI Overview for Managers
This course is intended for business managers, and decision-makers who want to understand AI technologies and lead successful AI initiatives in their organizations.
Prerequisites Course AI Overview for Managers
No technical background is required. Participants should have basic business knowledge and an interest in understanding how AI can transform organizations.
Realization Training AI Overview for Managers
The training combines theoretical instruction with interactive discussions, and practical exercises guided by a trainer. Focus is on strategic decision-making and actionable insights.
AI Overview for Managers Certificate
After successful completion, participants receive a certificate of participation in AI Overview for Managers.
Modules
Module 1: AI Fundamentals
What is AI
Machine Learning Basics
Deep Learning Concepts
Generative AI
Large Language Models
AI vs Traditional Software
AI Capabilities
AI Limitations
Current AI Landscape
Future Trends
Module 2: Business Applications
AI Use Cases
Customer Service Automation
Marketing and Sales
Operations Optimization
Data Analysis
Decision Support Systems
Process Automation
Competitive Advantages
Industry Examples
ROI Considerations
Module 3: Implementation Strategy
AI Readiness Assessment
Data Requirements
Technology Stack
Build vs Buy
Vendor Selection
Proof of Concept
Pilot Projects
Change Management
Team Building
Success Metrics
Module 4: Leadership and Governance
Ethical Considerations
Responsible AI
Data Privacy
Regulatory Compliance
Risk Management
AI Governance
Stakeholder Communication
Budget Planning
Long-Term Strategy
Action Planning
€799
Klassikaal
max 12
1 dag
Vibe Coding
Amsterdam
vr 17 jul. 2026
en 9 andere data
The course Vibe Coding from SpiralTrain teaches you how to code with AI-powered voice and natural language using Vibe IDE.
Vibe Fundamentals
The course Vibe Coding begins with an overview of Vibe IDE including installation, interface navigation, voice activation setup, microphone configuration, audio settings, command recognition, natural language processing capabilities, and comparison with traditional IDEs.
Voice Coding
This module covers voice-driven coding including voice commands, dictation mode, code generation through speech, creating functions and variables, defining control structures, error correction, code navigation, refactoring commands, and generating documentation via voice.
Multimodal Development
Here participants learn multimodal capabilities including screen sharing, visual context understanding, image input, generating code from screenshots, converting diagrams to code, whiteboard integration, gesture control, multi-input workflows, and collaboration features.
Production Workflows
The course concludes with production-ready workflows including development patterns, team collaboration, code quality practices, voice-driven debugging, testing strategies, version control integration, performance optimization, accessibility considerations, and productivity optimization tips.
Audience Course Vibe Coding
This course is intended for developers, and technical professionals who want to explore voice-driven development and leverage AI interactions to accelerate their coding workflow.
Prerequisites Course Vibe Coding
Participants should have basic programming experience. Clear speech and a quiet environment are beneficial.
Realization Training Vibe Coding
The training combines theoretical instruction with hands-on voice coding exercises guided by a trainer. Participants build applications using voice commands and multimodal interactions.
Vibe Coding Certificate
After successful completion, participants receive a certificate of participation in Vibe Coding.
Modules
Module 1: Vibe Fundamentals
Vibe IDE Overview
Installation and Setup
Interface Navigation
Voice Activation
Microphone Configuration
Audio Settings
Command Recognition
Natural Language Processing
Vibe vs Traditional IDEs
Best Practices
Module 2: Voice Coding
Voice Commands
Dictation Mode
Code Generation
Function Creation
Variable Declaration
Control Structures
Error Correction
Code Navigation
Refactoring Commands
Documentation via Voice
Module 3: Multimodal Development
Screen Sharing
Visual Context
Image Input
Code from Screenshots
Diagram to Code
Whiteboard Integration
Gesture Control
Multi-Input Workflows
Context Switching
Collaboration Features
Module 4: Production Workflows
Development Patterns
Team Collaboration
Code Quality
Debugging with Voice
Testing Strategies
Version Control
Performance Optimization
Accessibility Considerations
Productivity Tips
Hands-On Projects
€799
Klassikaal
max 12
1 dag
App Development with Cursor
Amsterdam
vr 24 jul. 2026
en 9 andere data
The course App Development with Cursor from SpiralTrain teaches you how to accelerate application development using Cursor AI-powered IDE.
Cursor Fundamentals
The course App Development with Cursor begins with an overview of Cursor IDE including installation, interface navigation, workspace configuration, extensions, keyboard shortcuts, AI features overview, and comparison with traditional editors.
AI-Assisted Coding
This module covers AI-powered coding features including intelligent code completion, natural language commands, code generation, inline chat, Composer mode, context awareness, multi-file editing, code suggestions, error detection, and automated documentation generation.
Advanced Features
Here participants learn advanced capabilities including codebase indexing, chat with entire codebase, terminal integration, AI-assisted debugging, refactoring tools, automated test generation, code review features, Git integration, and custom instructions.
Production Workflows
The course concludes with production-ready workflows including project templates, development patterns, team collaboration, code quality practices, performance optimization, security considerations, deployment preparation, version control strategies, and productivity optimization tips.
Audience Course App Development with Cursor
This course is intended for software developers, and technical professionals who want to accelerate their development workflow using Cursor's AI features.
Prerequisites Course App Development with Cursor
Participants should have basic programming experience. Familiarity with code editors and development workflows is beneficial.
Realization Training App Development with Cursor
The training combines theoretical instruction with hands-on exercises guided by an expert trainer. Participants build real applications using Cursor's AI features.
App Development with Cursor Certificate
After successful completion, participants receive a certificate of participation in App Development with Cursor.
Modules
Module 1: Cursor Fundamentals
Cursor Overview
Installation and Setup
Interface Navigation
Workspace Configuration
Extensions and Plugins
Keyboard Shortcuts
AI Features Overview
Cursor vs VS Code
Pricing and Licenses
Best Practices
Module 2: AI-Assisted Coding
AI Code Completion
Natural Language Commands
Code Generation
Inline Chat
Composer Mode
Context Awareness
Multi-File Editing
Code Suggestions
Error Detection
Documentation Generation
Module 3: Advanced Features
Codebase Indexing
Chat with Codebase
Terminal Integration
Debugging with AI
Refactoring Tools
Test Generation
Code Review
Git Integration
Custom Instructions
Privacy Settings
Module 4: Production Workflows
Project Templates
Development Patterns
Team Collaboration
Code Quality
Performance Optimization
Security Considerations
Deployment Preparation
Version Control
Productivity Tips
Hands-On Projects
€799
Klassikaal
max 12
1 dag
Agentic AI with CrewAI
Amsterdam
ma 3 aug. 2026
en 9 andere data
The course Agentic AI with CrewAI from SpiralTrain teaches you how to build sophisticated multi-agent AI systems using the CrewAI framework.
CrewAI Fundamentals
The course Agentic AI with CrewAI begins with an overview of CrewAI and multi-agent concepts. Installation, core components, agent basics, crew structure, task fundamentals, process types, and sequential workflows are explored.
Agent Design
This module covers designing effective agents including defining roles, goals, backstories, creating specialized agents, delegation strategies, autonomy levels, agent memory, personality design, communication styles, and agent development best practices.
Tasks and Workflows
Here participants learn task definition including descriptions, expected outputs, dependencies, context management, callbacks, error handling, validation, asynchronous tasks, and optimization strategies for efficient workflow execution.
Tools Integration
This part focuses on integrating tools including built-in tools, custom tool creation, API integration, search capabilities, file operations, database access, web scraping, code execution, error handling, and tool best practices.
Advanced Orchestration
Advanced orchestration patterns are addressed including hierarchical processes, manager agents, conditional workflows, parallel execution, dynamic crew building, agent handoffs, workflow branching, optimization, and complex orchestration patterns.
Memory Systems
Memory management is explored covering short-term and long-term memory, entity memory, conversation history, storage solutions, retrieval strategies, context management, optimization, shared knowledge systems, and state persistence.
Production Deployment
Deployment considerations include strategies, environment configuration, API development, monitoring, logging, error recovery, performance optimization, cost management, security, testing strategies, and production deployment checklists.
Real-World Applications
Practical applications are covered including research automation, content generation, data analysis, customer service, marketing campaigns, business intelligence, process automation, decision support systems, industry-specific solutions, and case studies.
Advanced Topics
The course concludes with advanced subjects including human-in-the-loop systems, guardrails implementation, quality assurance, agent evaluation, prompt optimization, LLM integration, CrewAI ecosystem, troubleshooting, future trends, and capstone project.
Audience Course Agentic AI with CrewAI
This course is intended for AI developers, software engineers, and data scientists who want to build multi-agent AI systems using CrewAI.
Prerequisites Course Agentic AI with CrewAI
Participants should know Python programming and understand of AI and LLM concepts. Familiarity with prompt engineering and API integration is beneficial.
Realization Training Agentic AI with CrewAI
The training combines theoretical instruction with hands-on labs guided by a trainer. Participants build real multi-agent systems throughout the course.
Agentic AI with CrewAI Certificate
After successful completion, participants receive a certificate of participation in Agentic AI with CrewAI.
Modules
Module 1: CrewAI Fundamentals
CrewAI Overview
Multi-Agent Concepts
Installation and Setup
Core Components
Agent Basics
Crew Structure
Task Fundamentals
Process Types
Sequential Workflows
Best Practices
Module 2: Agent Design
Agent Roles
Agent Goals
Agent Backstory
Specialized Agents
Agent Delegation
Autonomy Levels
Agent Memory
Agent Personality
Communication Styles
Agent Best Practices
Module 3: Tasks and Workflows
Task Definition
Task Description
Expected Output
Task Dependencies
Task Context
Task Callbacks
Error Handling
Task Validation
Async Tasks
Task Optimization
Module 4: Tools Integration
Built-in Tools
Custom Tool Creation
API Integration
Search Tools
File Operations
Database Access
Web Scraping
Code Execution
Tool Error Handling
Tool Best Practices
Module 5: Advanced Orchestration
Hierarchical Process
Manager Agents
Conditional Workflows
Parallel Execution
Dynamic Crew Building
Agent Handoffs
Workflow Branching
Process Optimization
Complex Orchestration
Workflow Patterns
Module 6: Memory Systems
Short-Term Memory
Long-Term Memory
Entity Memory
Conversation History
Memory Storage
Memory Retrieval
Context Management
Memory Optimization
Shared Knowledge
State Persistence
Module 7: Production Deployment
Deployment Strategies
Environment Configuration
API Development
Monitoring and Logging
Error Recovery
Performance Optimization
Cost Management
Security Considerations
Testing Strategies
Production Checklist
Module 8: Real-World Applications
Research Automation
Content Generation
Data Analysis
Customer Service
Marketing Campaigns
Business Intelligence
Process Automation
Decision Support
Industry Solutions
Case Studies
Module 9: Advanced Topics
Human-in-the-Loop
Guardrails Implementation
Quality Assurance
Agent Evaluation
Prompt Optimization
LLM Integration
CrewAI Ecosystem
Troubleshooting
Future Trends
Capstone Project
€2.250
Klassikaal
max 12
3 dagen
Model Context Protocol
Amsterdam
do 30 jul. 2026
en 9 andere data
The course Model Context Protocol from SpiralTrain teaches you how to build AI applications that seamlessly connect to external data sources and tools using the standardized Model Context Protocol.
MCP Fundamentals
The course Model Context Protocol starts with an overview of the protocol including the AI context problem, JSON-RPC foundation, transport mechanisms, resource concepts, tool definitions, and real-world use case examples.
Protocol Architecture
Next the architecture patterns are explored, covering communication flow, message types, capability negotiation, session management, error handling, connection lifecycle, protocol extensions, and versioning strategies for robust implementations.
Server Implementation
This module covers building MCP servers including SDK installation, implementing resource providers, developing and registering tools, context management, data source integration, authentication methods, configuration options, and comprehensive testing approaches.
Client Development
Here participants learn to build MCP clients including SDK integration, connection management, server discovery, resource access patterns, tool invocation, prompt usage, response handling, state management, and error recovery mechanisms.
Integration Patterns
This part focuses on integrating MCP with LLMs such as Claude and OpenAI. Topics include context injection, multi-server setups, fallback strategies, caching mechanisms, rate limiting, and monitoring solutions.
Production Deployment
The course concludes with production deployment strategies including containerization, scaling solutions, load balancing, security hardening, API gateway setup, version management, documentation standards, testing strategies, monitoring tools, and hands-on production projects.
Audience Course Model Context Protocol
This course is intended for AI developers, and software architects who want to build AI applications that connect to external data sources and tools using the Model Context Protocol.
Prerequisites Course Model Context Protocol
Participants should have solid programming experience in Python or TypeScript and understanding of API development.
Realization Training Model Context Protocol
The course combines theoretical sessions with hands-on labs guided by a trainer. Real-world case studies are central to the training experience.
Model Context Protocol Certificate
After completion, participants receive a certificate of participation in Model Context Protocol.
Modules
Module 1: MCP Fundamentals
MCP Protocol Overview
AI Context Problem
Protocol Specifications
JSON-RPC Foundation
Transport Mechanisms
Client-Server Model
Resource Concepts
Tool Definitions
Prompt Templates
Use Case Examples
Security Basics
Module 2: Protocol Architecture
Architecture Patterns
Communication Flow
Message Types
Request-Response Cycle
Capability Negotiation
Session Management
Error Handling
Connection Lifecycle
Protocol Extensions
Versioning Strategy
Best Practices
Module 3: Server Implementation
Server Setup
SDK Installation
Resource Providers
Implementing Resources
Tool Development
Tool Registration
Context Management
Data Source Integration
Authentication Methods
Configuration Options
Testing Servers
Module 4: Client Development
Client Setup
SDK Integration
Connection Management
Server Discovery
Resource Access
Tool Invocation
Prompt Usage
Response Handling
State Management
Error Recovery
Performance Optimization
Module 5: Integration Patterns
LLM Integration
Claude Integration
OpenAI Integration
Context Injection
Multi-Server Setup
Fallback Strategies
Caching Mechanisms
Rate Limiting
Monitoring Solutions
Logging Practices
Real-World Examples
Module 6: Production Deployment
Deployment Strategies
Containerization
Scaling Solutions
Load Balancing
Security Hardening
API Gateway Setup
Version Management
Documentation Standards
Testing Strategies
Monitoring Tools
Production Projects
€1.699
Klassikaal
max 12
2 dagen
Actualiteitencursus medische aspecten in de asielprocedure
Utrecht
di 15 dec. 2026
Laat je overtuigen door de gratis podcast
Inhoud
Introductie;
Gezondheidsproblemen asielzoekers;
Medisch advies en medische beperkingen;
Werkinstructie: handelen IND en advocaat;
Werkinstructies 2014/10 en 2015/8;
Jurisprudentie medisch advies;
Forensisch medisch onderzoek en iMMO;
Medische informatie opvragen;
Jurisprudentie medisch steunbewijs;
EVRM medisch inclusief Dublin medische aspecten;
EHRM Paposhvili, WBV 2017/8;
Art. 64 Vw en werkinstructie 2018/16.
Medische aspecten de podcast
Asielzoekers in Nederland vragen bescherming in Nederland vanwege de schendingen van hun mensenrechten die hen zijn overkomen door oorlog, marteling of ander geweld. In de asielprocedure toetst de Immigratie en Naturalisatiedienst (IND) hun vraag om bescherming aan de internationale en nationale wet- en regelgeving.
Het nagaan van de geloofwaardigheid van de asielaanvraag wordt bepaald door met name de analyse van het asielverhaal dat de asielzoeker vertelt aan de IND. De asielzoeker zit vaak met een bewijsnood; hij of zij beschikt niet over andere bewijsmiddelen dan het relaas over de herinneringen van de ervaringen die tot de vlucht hebben geleid. Medische aspecten spelen bij de asielbeoordelingen een belangrijke rol en wel op diverse manieren. De praktijk laat zien dat het vaak lastig is om deze medische aspecten goed in te passen in de juridische kaders van de asielprocedure. Ook advocaten vinden het niet eenvoudig om deze niet-juridische aspecten goed te gebruiken in hun werk voor de asielzoekers.
Wil je alvast een voorproefje op deze cursus? In onze podcast: Recht.Vaardig de podcast, sprak Paul Tillemans, directeur new business bij OSR, de
Datum: 15 december 2026 10:00-16:30
WO
€650
Klassikaal
max 24
1 dag
Actualiteitencursus mensenhandel voor asiel- en vreemdelingenadvocaten
Nog niet bekend
do 26 nov. 2026
Vanuit het perspectief van zowel de advocatuur als de IND
Programma
definitie en ontwikkelingen nationaal en internationaal niveau;
signalering/identificatie en herkennen van geringe indicaties;
actoren en processen;
beschermde opvang;
koppeling asielprocedure;
opvang voor slachtoffers mensenhandel;
samenloop B8 procedure en asielprocedure;
mensenhandel binnen de asielprocedure;
mensenhandel als grond voor vervolging of ernstige schade;
Dublinprocedure en mensenhandel;
jurisprudentie.
Wat zijn de gevolgen van mensenhandel voor een asielprocedure?
Als asieladvocaat word je op verschillende manieren geconfronteerd met slachtofferschap mensenhandel. Wat is mensenhandel en welke ontwikkelingen vinden plaats op internationaal en nationaal gebied? Hoe kunnen signalen worden herkend en welke procedures bestaan er? Welke rol speelt mensenhandel binnen de asielprocedure en welke samenloop tussen verschillende procedures bestaan er? Op welke wijze wordt mensenhandel beoordeeld binnen de asielprocedure en kunnen verklaringen omtrent mensenhandel een grond vormen voor vluchtelingschap, vervolging of ernstige schade? Hoe spelen verklaringen omtrent mensenhandel een rol binnen de Dublinprocedures?
In deze cursus zal worden ingegaan op verschillende juridische en praktische onderwerpen en zal ruimte zijn voor discussie en het delen van ervaringen uit de praktijk. De cursus zal worden gegeven door een medewerker van de Immigratie- en Naturalisatiedienst en een advocaat, zodat de praktijk vanuit verschillende hoeken wordt belicht.
Deze actualiteitencursus is verplicht voor jouw aantekening mensenhandel van de Raad voor Rechtsbijstand (RvR).
Voor wie is deze cursus
Datum: 26 november 2026 10:15-16:30
WO
€650
Klassikaal
max 24
1 dag
Verdiepingscursus privacy in de personenschade
Utrecht
vr 18 sep. 2026
en 1 andere data
Belangrijker dan ooit: privacy-proof omgaan met persoonsgegevens in personenschadezaken
Programma:
AVG en UAVG algemeen;
Medische Paragraaf en Gedragscode behandeling Letselschade;
Gedragscode Verwerking Persoonsgegevens Verzekeraars;
Praktijkvragen casustiek
Werkwijze
Theorie over de AVG en UAVG en de gedragscodes in de personenschade
Interactieve bijeenkomst aan de hand van dilemmas en casustiek
Verwerken van persoonsgegevens
Wanneer is het delen van een medisch advies met de arbeidsdeskundige toegestaan? Mag de verzekeraar de schadebehandeling zomaar aan een schaderegelingsbureau uitbesteden? Waar moet ik op letten wanneer ik gegevens wil uitwisselen bij regres? En hoe moet ik omgaan met het BSN?
Deze en tal van andere vragen spelen in de letselschaderegeling een belangrijke rol.
Bij het behandelen van letselschade worden veel persoonsgegevens verwerkt. Vrijwel altijd is het beoordelen van vertrouwelijke informatie nodig om een schade af te kunnen wikkelen. Dit geldt in het bijzonder voor de medische gegevens van het slachtoffer.
Verzekeraars, schaderegelingsbureaus en belangenbehartigers van benadeelden moeten in het kader van het gebruik en de uitwisseling van (gevoelige) persoonsgegevens voldoen aan de strenge verplichtingen van de Algemene Verordening Gegevensbescherming (AVG en UAVG) en de diverse regels uit de personenschadebranche, zoals de Medische Paragraaf van de GBL.
In deze verdiepingscursus geeft de docent inzicht in hoe je “privacy-proof” omgaat met de uitwisseling van (gevoelige) persoonsgegevens in personenschadezaken. We bespreken d
Datum: 18 september 2026 10:00-13:00 Datum: 8 december 2026 10:00-13:00
WO
€400
Klassikaal
max 20
1 dag