Opleidingen
68.951
resultaten
Masterclass leiderschapsanalyse
Doelgroep
Actuarieel professionals in een leidinggevende rol.
Hoe zorg je dat jouw manier van leidinggeven naadloos aansluit bij de strategische ambities van je organisatie? Tijdens deze masterclass leer je de onderliggende logica van jouw organisatie beter begrijpen: hoe worden keuzes gemaakt, waar zit de beweging en welke rol kun jij daarin spelen? Je krijgt praktische handvatten om krachtig én inspirerend leiding te geven, met meer invloed, richting en impact.
Doel
De masterclass helpt je om bewuster te worden van het ‘waartoe’ van jouw leiderschap in jouw organisatie. Je krijgt helder inzicht in de organisatielogica die jouw organisatie bij elkaar houdt en inspiratie om jouw leiderschapsrol effectief af te stemmen op de strategische ambities. Daarnaast leer je hoe je samenwerking zo organiseert dat interne belangen en externe verwachtingen elkaar versterken in plaats van tegenwerken.
Spreker
David Breugem is organisatieduider en registeraccountant met ruim 35 jaar ervaring als accountant, hrm-strateeg en organisatieadviseur. Daarnaast ontwikkelde hij het Organisatielogica-model om leiderschap beter te laten aansluiten op organisatiedoelen.
€375
Klassikaal
3 uren
Masterclass Neuromarketing in de candidate journey
Wist je dat een simpele toevoeging in een vacaturetekst 62% meer sollicitanten oplevert? Dat je het bezoekersgedrag op jouw werkenbij-site kan sturen? En dat je zelfs ghosting door kandidaten kan voor
Nicol Tadema deelt diverse beïnvloedingstechnieken de je direct de volgende (werk)dag in de praktijk kan toepassen. Dit zijn technieken die aansluiten bij 7 fases in de candidate journey: van het trekken van de aandacht tot het aanzetten tot actie.
De beïnvloedingstechnieken zijn gericht op het onbewuste brein. Want… in een wereld die in een duizelingwekkend tempo verandert, blijft er 1 ding vrijwel hetzelfde. Dat is de manier waarop mensen keuzes en beslissingen nemen. Die keuzes en beslissingen worden in 98% van de gevallen gemaakt op de automatische piloot, instinct en op het gevoel. En ja, dit gebeurt ook als talent kiest om te reageren op jouw vacature én niet op de vacature van een concurrent. Ook bij het activeren van een job alert, een reply op een InMail of een like op een socialmediapost speelt het onbewuste brein een hoofdrol.
Ontdek hoe de kracht van invloed werkt én met welke kleine wijzigingen jij een reusachtig resultaat kan boeken.
Wist je dat… ‘sociale invloed’ een plek scoort in de top 3 van meest gewilde vaardigheden van werkgevers? Sociale invloed is de vaardigheid om anderen effectief te beïnvloeden, te motiveren en te inspireren. Bron: Future of Jobs Rapp
€795
Klassikaal
max 16
1 dag
Masterclass Werven met TikTok, Shorts en Reels
Vergroot jouw wervingssucces met het snelst groeiende socialmedia platform: TikTok.
Als recruiter en arbeidsmarktcommunicatiespecialist is het essentieel om op de hoogte te blijven van de nieuwste trends en technologieën. TikTok, het snelgroeiende sociale mediaplatform, heeft de manier waarop we content bekijken en delen drastisch veranderd. Maar wist je dat TikTok niet alleen een bron van entertainment is, maar ook een krachtig hulpmiddel kan zijn voor werving en employer branding?
Deze masterclass is speciaal ontworpen voor recruiters, HR-professionals en arbeidsmarktcommunicatiespecialisten die hun wervingsstrategieën willen versterken door TikTok effectief in te zetten. We behandelen hoe je TikTok kunt gebruiken om talent aan te trekken en betrokkenheid te vergroten bij zowel je huidige werknemers als potentiële kandidaten. Je leert hoe je op een creatieve en authentieke manier kunt opvallen op TikTok en hoe je deze krachtige tool kunt integreren in je bestaande strategie.
€495
Klassikaal
max 20
1 dag
Strategisch recruitment in de praktijk
Rotterdam
ma 1 jun. 2026
Leer hoe je recruitment strategisch maakt en aanpakt én direct toepast in de praktijk. Deze hands-on training combineert fundamentele recruitmentprincipes met de nieuwste ontwikkelingen, waarbij je le
Introductie
In de hedendaagse wereld van schaarste, tekorten en ‘de war for talent’ binnen talent acquisition is een strategische kijk en aanpak van recruitment essentieel. Deze tweedaagse training 'Strategisch Recruitment in de praktijk' biedt je de handvatten om recruitment naar een modern en hoog niveau te tillen, waarbij we de balans vinden tussen strategisch denken en directe toepasbaarheid. We focussen op het operationeel strategische aspect, wat de training toegankelijk en praktijkgericht maakt.
Wat deze training uniek maakt, is dat we je niet simpelweg antwoorden geven op je vragen - die kun je immers ook via AI-tools verkrijgen. In plaats daarvan bieden we je de essentiële context en inzichten om zelf actuele en moderne oplossingen te ontwikkelen. Je leert hoe je recruitment kunt positioneren als strategische partner binnen je organisatie en hoe je inspeelt op de nieuwste ontwikkelingen in het vakgebied. Gewapend met de kennis om de juiste vragen te stellen en de antwoorden in de juiste context te plaatsen, krijg je diepgaand inzicht in de kracht van data, visie, analyse en het hebben van een verhaal in recruitment.
Programma
Elke dag bestaat uit twee blokken van 3
€1.999
Klassikaal
max 16
2 dagen
Masterclass Vacatureteksten en AI
Een goede vacaturetekst is online vindbaar, spreekt de doelgroep aan, pre selecteert en zet aan tot solliciteren. Tijdens deze training leer je doelgroepgerichte en wervende vacatureteksten te schrijv
Vacatureteksten zijn nog steeds het meest gebruikte middel binnen arbeidsmarktcommunicatie en recruitment. Tijdens deze masterclass krijg je handvatten om je vacatureteksten te optimaliseren. Van doelgroepgerichtheid tot online vindbaarheid (SEO). Van optimale indeling tot selecterend vermogen. Daarnaast staan we stil bij AI en hoe jij kunstmatige intelligentie kunt gebruiken om inspiratie op te doen voor jouw vacatureteksten.
Tijdens deze masterclass breng je de theorie direct in de praktijk middels opdrachten en oefeningen met jouw eigen vacatureteksten. Tenslotte kun je na afloop een herschreven vacaturetekst voorleggen aan de docent voor een-op-een feedback
€559
Klassikaal
max 16
1 dag
Implementing an AI Maturity Plan [GK840041]
VIRTUAL TRAINING CENTER
ma 29 jun. 2026
en 4 andere data
OVERVIEW
Lead with confidence—build and execute a strategic AI maturity plan for your organization.
Artificial intelligence is no longer a distant frontier—it’s a present-day imperative for organizations seeking to remain competitive, innovative, and resilient. Yet, successful AI adoption isn’t just about deploying technology; it requires a deliberate, phased approach rooted in strategic alignment, organizational readiness, and leadership commitment. Implementing an AI Maturity Plan is an intensive course designed specifically for senior leaders and decision-makers who are ready to take ownership of their organization’s AI journey and drive meaningful transformation.
This course goes beyond theory to equip participants with a structured framework for assessing their current AI maturity, identifying strategic enablers and barriers, and crafting a tailored roadmap for progression. It emphasizes the critical pre-work required—such as gathering organizational data, aligning leadership, and reviewing existing initiatives—so that participants arrive prepared to engage deeply and collaboratively. Through guided exercises, case studies, and peer exchange, leaders will learn how to navigate the four phases of AI maturity, from exploration to realization, and how to lead change across culture, governance, and capability development. The course is designed to challenge assumptions, foster strategic clarity, and empower leaders to build scalable, responsible, and future-ready AI strategies.
OBJECTIVES
Remember (Foundational Knowledge)
Recall the four phases of AI maturity
Identify key characteristics of each AI maturity phase
Recognize fundamental AI technologies and their potential applications
Understand (Comprehension and Interpretation)
Explain the strategic importance of AI maturity
Describe the progression between AI maturity phases
Interpret the impact of AI on organizational strategy
Summarize the challenges and opportunities in AI adoption
Apply (Practical Implementation)
Develop a preliminary AI maturity roadmap for their organization
Create strategies for transitioning between AI maturity phases
Implement initial AI assessment and planning techniques
Adapt AI strategies to specific organizational contexts
Analyze (Critical Thinking and Evaluation)
Compare and contrast different approaches to AI implementation
Examine the potential risks and benefits of AI adoption
Evaluate current organizational AI capabilities
Diagnose barriers to AI integration and innovation
Evaluate (Strategic Decision-Making)
Assess the potential business value of AI initiatives
Critique existing AI strategies and implementation approaches
Judge the readiness of an organization for AI transformation
Validate AI investment and implementation strategies
Create (Innovation and Strategic Planning)
Design a comprehensive AI maturity transformation plan
Construct a forward-looking AI strategy
Synthesize cross-functional AI implementation approaches
Propose innovative AI-driven business solutions
AUDIENCE
Strategic Leaders and Decision-Makers Across Organizational Levels
Ideal Participants Include:
- C-Suite Executives
- Senior Leadership
- Operational Leadership
- Functional Area Leaders
- Cross-Functional Roles
- Emerging Leadership Roles
CONTENT
1. Understanding AI Maturity
What AI maturity means and why it matters
Overview of the four AI maturity phases
Self-assessment: identifying your organization’s current phase
2. Exploring the Maturity Journey
Deep dive into each phase: Exploration, Experimentation, Innovation, Realization
Common patterns, barriers, and enablers across phases
3. Strategic Planning and Roadmapping
Building a tailored AI maturity roadmap
Aligning strategy, governance, and resources
Managing transitions and scaling AI initiatives
4. Leadership in AI Transformation
Leading change across culture and capability
Communication and trust-building strategies
Leadership competencies for each maturity phase
5. Emerging Trends and Continuous Learning
Key AI technologies and industry trends
Creating a sustainable AI learning culture
Final action planning and roadmap development
€795
Klassikaal
max 16
Advanced Concepts of Data Visualization [GK840042]
Eindhoven (Evoluon Noord Brabantlaan 1)
do 18 jun. 2026
en 6 andere data
OVERVIEW
Learn to design powerful, interactive dashboards and visual stories that turn complex data into clear, actionable insights.
Advanced Concepts in Data Visualization is a three-day immersive course designed for professionals who want to elevate their data storytelling and dashboard design skills. Building on foundational visualization principles, this course dives into advanced chart types, ethical design practices, and the role of the author in shaping how data is understood. Learners will explore how design decisions—like color usage, annotation, and layout—can dramatically impact the clarity and effectiveness of a visual narrative.
Throughout the course, participants will gain hands-on experience with interactive dashboards, live data pipelines, and mobile optimization techniques. They’ll learn to implement features like slicers, tooltips, bookmarks, and row-level security, while also developing a deeper understanding of how to transform and model data using Power Query and DAX. By the end of the course, learners will be equipped not just to build dashboards, but to craft compelling visual arguments that resonate with their audience and support confident decision-making.
OBJECTIVES
Create compelling visual narratives that effectively communicate insights and drive decision making
Discuss and implement best practices for designing impactful charts and dashboards and practice making design decisions that support a visualization goal
Recognize specialized chart types and examine different forms of interactivity
Use advanced chart types (networks, waterfall charts, small multiples, stream graphs, combination line and bar charts) and custom visuals to extend visualization capabilities in Power BI
Use conditional formatting, cross-filtering/highlighting, buttons, slicers, tooltips, and bookmarks to increase interactivity and communication efficacy in Power BI
Understand and construct a data pipeline to create an updatable dashboard
Recognize the opportunities and challenges of live-updating dashboards, and how to mitigate associated risks
Use Power Query Editor and DAX formulas for data transformation and calculated fields in Power BI
Implement data model view, parameters, and incremental refresh for handling and organizing dynamic and large datasets in Power BI
Optimize dashboards and other data visualizations for mobile view in Power BI: prioritize visualizations for smaller space, touch-friendly interface, and progressive disclosure.
Implement row level security to limit access and create secure visualizations in PowerBI
AUDIENCE
Data visualization practitioners: learners who make data visualizations as part of their role (in any sector or context) can level up their communication skills, design thinking, and technical know-how with this course.
Data analysts with knowledge of PowerBI and basic data viusalization: analysts with an interest in visualzation can develop expertise in data visualization, design thinking, and PowerBI.
Data analysts or visualization practitioners who want to design end-to-end data pipelines for continuously updating data visualizations / dashboards.
As well as: Business Intelligence Professionals, Data Scientists, and Business Analysts
CONTENT
Advanced Chart Types & Visual Design
Explore the role of design in effective data communication
Apply color theory and accessibility principles to visualizations
Learn and implement advanced chart types in Power BI:
Networks, waterfall charts, small multiples, stream graphs, and combo charts
Practice ethical visualization and understand the author’s influence on interpretation
Interactivity & Live Data Dashboards
Design interactive dashboards using slicers, tooltips, bookmarks, and conditional formatting
Understand and build data pipelines for live/updatable dashboards
Use Power Query and DAX for data transformation and calculated fields
Implement best practices for designing user-friendly, interactive experiences
Visual Storytelling & Publishing
Craft visual arguments that align with audience needs and business goals
Optimize dashboards for mobile viewing and touch-friendly interfaces
Apply row-level security to protect sensitive data
Publish and maintain dashboards with confidence, including versioning and troubleshooting
€1.495
Klassikaal
max 16
Applied Computer Vision Essentials [GK840043]
VIRTUAL TRAINING CENTER
ma 8 jun. 2026
en 4 andere data
OVERVIEW
Learn to build, deploy, and evaluate modern computer vision systems—from classical techniques to cutting-edge deep learning.
Applied Computer Vision Essentials is a hands-on course designed for professionals eager to deepen their understanding of modern computer vision techniques. Whether you're transitioning from classical image processing or already working with deep learning models, this course offers a structured path to mastering the tools and concepts that power today’s most advanced visual systems. From edge detection and feature extraction to segmentation and multimodal pipelines, learners will explore the full spectrum of computer vision applications through practical labs and real-world scenarios.
Participants will gain experience with cutting-edge frameworks like YOLOv9, SAM 2, and DINOv2, while building and deploying models in a GPU-enabled Ubuntu environment. The course emphasizes not just technical proficiency but also ethical considerations, including bias auditing and production monitoring. With a curriculum that blends theory, demos, and capstone projects, learners will leave equipped to tackle challenges in domains ranging from industrial automation to health tech and retail analytics.
Ideal for software engineers, data scientists, and MLOps professionals, this course bridges the gap between foundational knowledge and applied expertise. Whether you're optimizing models for edge deployment or integrating vision with language models for safety reporting, Applied Computer Vision Essentials provides the skills and confidence to build robust, scalable solutions.
OBJECTIVES
Apply classical computer vision techniques for edge detection, feature extraction, and lane detecti
Analyze color spaces, histogram equalization, and contrast enhancement methods for image quality improvement
Create data augmentation pipelines and fine-tune CNN architectures like EfficientNet for classification
Evaluate object detection performance using mAP and IoU metrics with TIDE error analysis
Implement YOLO training workflows for safety compliance with hyperparameter optimization
Compare segmentation approaches from traditional methods to modern promptable SAM 2
Construct Vision Transformer solutions using DINOv2 and self-supervised learning principles
Synthesize multimodal pipelines integrating detection, CLIP embeddings, and language models for alt-text generation
Optimize models for production through ONNX conversion, INT8 quantization, and edge deployment
Assess computer vision systems for bias and fairness while implementing production monitoring with Prometheus
AUDIENCE
Sample learning personas:
Rajesh Singh – Senior software engineer, industrial-automation firm, Bengaluru, India. Uses classical OpenCV; needs a roadmap for defect and lane detection with deep learning.
Maria Alvarez – Data scientist, retail supply-chain analytics, Guadalajara, Mexico. Comfortable with PyTorch classifiers; wants hands-on object detection and edge deployment for PPE compliance.
Esther Ndiaye – Machine-learning engineer, health-tech start-up, Dakar, Senegal. NLP background; seeks robust instrument segmentation and guidance on regulatory alignment.
Lucas Chen – DevOps engineer moving into MLOps, Toronto, Canada. Strong in Docker and CI/CD; aims to learn model quantisation, monitoring, and bias auditing for a vision API.
CONTENT
Foundations & Classical Computer Vision
Pixels, color spaces, convolution filters
Lane‑finding with Canny + Hough
Histogram equalisation & CLAHE
Low‑light rescue with CLAHE
Feature extraction: classical descriptors
Image matching: ORB vs SIFT
CVAT annotation + COCO export
Wrap-up: bridging classical to modern CV
Deep Learning for Computer Vision
Classical to deep transition
CNN architectures & evolution
Data‑augmentation strategies
AutoAugment & RandAugment demo
Fine‑tune EfficientNet‑V2‑S + Grad‑CAM
Intro to object detection & YOLO family
YOLOv11‑nano training start
Detection metrics & interpretation; TIDE taxonomy
Model robustness discussion
Advanced Vision: Segmentation & Transformers
From detection to segmentation
Segmentation approaches
SAM 2: promptable segmentation
SAM 2 segmentation vs YOLO masks
Vision Transformers revolution
Video processing fundamentals
Attention rollout visualisation
Self-supervised learning
Fine‑tune DINOv2‑tiny
Modern CV landscape
Capstone prep
Modern Applications & Integration
Recap: CV evolution journey
Vision-language models
Image & video generation
Detector → CLIP → LLM safety report
Model deployment essentials
ONNX conversion & optimization
Production monitoring demo
Adversarial robustness
Ethics in Computer Vision
Wrap-up; Q&A
Capstone demos
€3.195
Klassikaal
max 16
Cybersecurity Specialization: Artificial Intelligence Risk Management Framework [GK840108]
VIRTUAL TRAINING CENTER
do 6 aug. 2026
en 3 andere data
OVERVIEW
Learn to navigate global AI risk and regulatory frameworks with confidence and clarity.
As artificial intelligence becomes increasingly embedded in critical systems, managing its risks is no longer optional—it’s essential. This two-day, hands-on course is designed to equip AI practitioners, cybersecurity professionals, risk managers, and compliance leaders with the tools and frameworks needed to navigate the complex landscape of AI risk. Participants will explore the structure and application of the NIST AI Risk Management Framework (AI RMF), compare it with global standards such as the EU AI Act and Saudi Arabia’s NCA AI & Data Governance Framework, and learn how to apply these principles to real-world scenarios.
Through a blend of expert-led instruction, interactive activities, and case-based exercises, learners will gain practical experience in identifying, assessing, and mitigating AI risks such as bias, explainability, and data privacy. The course emphasizes ethical governance and regulatory compliance, guiding participants in designing unified risk strategies that align with international standards. Whether you're building AI systems or overseeing their deployment, this course offers a comprehensive foundation for responsible and secure AI implementation.
OBJECTIVES
Identify key risks associated with AI systems, including bias, explainability, privacy, and robustness.
Describe the structure and components of the NIST AI Risk Management Framework (AI RMF).
Compare global AI governance frameworks, including the EU AI Act, NIST AI RMF, Saudi NCA AI Framework and OECD AI Principles.
Explain how AI risk categories (e.g., high-risk, unacceptable risk) are determined under the EU AI Act.
Analyze the alignment and divergence between NIST AI RMF, Saudi NCA AI Framework and the EU AI Act in addressing AI risk.
Apply NIST AI RMF functions (Map, Measure, Manage, Govern) to real-world AI use cases.
Evaluate AI governance strategies for ethical alignment and regulatory compliance.
Design a unified AI risk management strategy that addresses global compliance and cybersecurity needs.
Construct practical mitigation plans for identified AI risks, including monitoring and control mechanisms.
Collaborate in teams to assess AI risk scenarios and recommend strategy improvements.
Interpret real-world case studies to extract best practices and lessons learned for AI risk implementation.
AUDIENCE
This course is designed for AI practitioners, risk managers, cybersecurity professionals, compliance officers, policymakers, and organizational leaders involved in the development, deployment, or oversight of AI systems.
CONTENT
1- Introduction to AI Risk Management and Global Frameworks
Introduction to AI Risk Management
Overview of Key Global AI Frameworks
Mapping Global Frameworks to AI Risk Management Practices
AI Governance, Ethics, and Accountability
2- Advanced AI Risk Management Strategies and International Compliance
Advanced Risk Management Strategies for AI Systems
Regional Variations
Case Studies: AI RMF and EU AI Act Implementation
Designing a Global AI Risk Management Strategy
€1.595
Klassikaal
max 16
Using Wireshark to Analyze and Troubleshoot TCP/IP Networks [GK840150]
VIRTUAL TRAINING CENTER
ma 1 jun. 2026
en 6 andere data
OVERVIEW
Master the art of packet analysis and network troubleshooting with Wireshark in this immersive, hands-on course built for real-world challenges.
Using Wireshark to Analyze and Troubleshoot TCP/IP Networks is a hands-on course designed for IT professionals who want to sharpen their skills in network traffic analysis. The course blends theory with practical labs, guiding learners through capturing, filtering, and interpreting network packets using Wireshark. Participants will explore real-world scenarios involving performance bottlenecks, security threats, and protocol-specific behaviors, gaining the confidence to troubleshoot complex network issues.
Throughout the course, learners will build custom Wireshark profiles, apply advanced filtering techniques, and analyze traffic across wired and wireless networks. From identifying scanning activity and suspicious payloads to visualizing TCP trends and using command-line tools, the curriculum is structured to provide both foundational knowledge and advanced troubleshooting strategies. While not marketed as official certification prep, the course aligns well with the Wireshark Certified Analyst (WCA) exam objectives, making it a valuable resource for those pursuing certification or simply looking to deepen their expertise.
OBJECTIVES
Explain the purpose of network analysis and the role of Wireshark in troubleshooting, optimization, and security.
Describe Wireshark's functionality, including installation, configuration, and navigation.
Capture network traffic on wired and wireless networks, and apply capture filters to isolate specific traffic.
Analyze TCP/IP communications, including DNS, ARP, IPv4/IPv6, ICMP, UDP, and TCP traffic.
Create and apply display filters to focus on specific packets and interpret trace file statistics.
Follow streams and reassemble data for deeper analysis of conversations.
Customize Wireshark profiles for different analysis scenarios.
Annotate, save, export, and print packets for documentation and further analysis.
Use Wireshark’s expert system to identify and troubleshoot network issues.
Graph IO rates and TCP trends to visualize network performance.
Detect scanning and discovery processes, and analyze suspect traffic for security purposes.
Effectively use command-line tools for advanced network analysis.
AUDIENCE
- Network engineers, IT professionals, and cybersecurity practitioners aiming to learn network analysis and troubleshooting using Wireshark.
- Developers and administrators responsible for monitoring and managing network infrastructure effectively.
- Professionals seeking to implement best practices in network security and performance analysis with Wireshark
CONTENT
Introduction to Network Analysis and Wireshark
Overview of TCP/IP Analysis
Identifying Common Performance Issues
Installing and Updating Wireshark
Capturing Network Traffic
Network Forensics Overview
Network Forensics Techniques
Capture Methods and Filters
Analyzing Switched Networks
Using Network TAPs for Full-Duplex Links
Wireless Network Analysis
Configuring Capture Filters
Detect Scanning and Discovery Processes
Detecting Scanning and Discovery Processes
Customization and Advanced Navigation
Creating a Troubleshooting Profile
Setting Up a Custom Troubleshooting Profile
Customizing the User Interface
Adding Custom Columns and Configuring Preferences
Advanced Navigation Techniques
Building Permanent Coloring Rules
Creating and Applying Coloring Rules
Analyze Suspect Traffic
Analyzing Suspect Traffic
Time Values, Summaries, and Basic Statistics
Examining Delta Time
Setting Time References
Comparing Timestamp Values
Using TCP Conversation Timestamps
Enabling and Analyzing TCP Conversation Timestamps
Effective Use of Command-Line Tools
Using Command-Line Tools for Network Analysis
Protocol-Specific Traffic Analysis and Troubleshooting
Using Display Filters
Filtering Conversations and Endpoints
Building Filters Based on Packets
Building and Applying Packet-Based Filters
TCP/IP Communications and Resolutions
€3.195
Klassikaal
max 16