Artificial Intelligence (AI) voor managers - 2 dagen Training Cursus

LangGraph is a framework for building stateful, multi-actor LLM applications as composable graphs with persistent state and control over execution.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI platform engineers, DevOps for AI, and ML architects who wish to optimize, debug, monitor, and operate production-grade LangGraph systems.

By the end of this training, participants will be able to:

• Design and optimize complex LangGraph topologies for speed, cost, and scalability.
• Engineer reliability with retries, timeouts, idempotency, and checkpoint-based recovery.
• Debug and trace graph executions, inspect state, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces, deploy to production, and monitor SLAs and costs.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Advanced Ollama Model Debugging & Evaluation is an in-depth course focused on diagnosing, testing, and measuring model behavior when running local or private Ollama deployments.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI engineers, ML Ops professionals, and QA practitioners who wish to ensure reliability, fidelity, and operational readiness of Ollama-based models in production.

By the end of this training, participants will be able to:

• Perform systematic debugging of Ollama-hosted models and reproduce failure modes reliably.
• Design and execute robust evaluation pipelines with quantitative and qualitative metrics.
• Implement observability (logs, traces, metrics) to monitor model health and drift.
• Automate testing, validation, and regression checks integrated into CI/CD pipelines.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs and debugging exercises using Ollama deployments.
• Case studies, group troubleshooting sessions, and automation workshops.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Deze door een instructeur geleide live training (online of op locatie) is bedoeld voor professionals op geavanceerd niveau die veilige en efficiënte AI-gestuurde workflows willen implementeren met behulp van Ollama.

Aan het einde van deze training kunnen de deelnemers:

• Ollama implementeren en configureren voor privé AI-verwerking.
• AI-modellen integreren in veilige bedrijfsworkflows.
• AI-prestaties optimaliseren terwijl gegevensprivacy wordt behouden.
• Bedrijfsprocessen automatiseren met on-premise AI-capaciteiten.
• Zorgen voor naleving van bedrijfsveiligheids- en governancebeleid.

Deze door een instructeur geleide, live training in Nederland (online of op locatie) is bedoeld voor professionals op beginner-niveau die Claude AI in hun dagelijkse workflows willen integreren om de efficiëntie en automatisering te verbeter

Aan het einde van deze training zullen de deelnemers in staat zijn om:

• Claude AI te gebruiken voor het automatiseren van repetitieve taken en het stroomlijnen van workflows.
• De persoonlijke en teamproductiviteit te verbeteren met AI-gestuurde automatisering.
• Claude AI te integreren met bestaande bedrijfstools en -platforms.
• AI-gestuurde besluitvorming en taakbeheer te optimaliseren.

Deze door een instructeur geleide, live training in Nederland (online of op locatie) is bedoeld voor professionals op gemiddeld niveau die LLMs willen implementeren, optimaliseren en integreren met behulp van Ollama.

Aan het einde van deze training kunnen deelnemers:

• LLMs opzetten en implementeren met behulp van Ollama.
• AI-modellen optimaliseren voor prestaties en efficiëntie.
• GPU-versnelling benutten voor verbeterde inferentiesnelheden.
• Ollama integreren in workflows en applicaties.
• De prestaties van AI-modellen in de gaten houden en onderhouden.

Deze door een instructeur geleide, live training (online of ter plaatse) is gericht op beginners tot gemiddelde onderzoekers en laboratoriumprofessionals die wensen om beelden te verwerken en te analyseren die betrekking hebben op histologische weefsels, bloedcellen, algen en andere biologische monsters.

Aan het einde van deze training zullen de deelnemers in staat zijn om:

• De interface van Fiji te navigeren en de kernfuncties van ImageJ te gebruiken.
• Wetenschappelijke beelden te voorverwerken en te verbeteren voor een betere analyse.
• Beelden kwantitatief te analyseren, inclusief celtelling en oppervlaktemeting.
• Herhaalde taken te automatiseren met behulp van macros en plug-ins.
• Werkstroomprocessen aan te passen aan specifieke beelddanalyseeisen in biologische onderzoek.

Deze door een instructeur geleide, live training (online of ter plaatse) is bedoeld voor geavanceerde professionals die hun AI-modellen op Ollama willen verfijnen en aanpassen voor verbeterde prestaties en specifieke toepassingen binnen hun domein.

Aan het einde van deze training zullen de deelnemers in staat zijn om:

• Een efficiënte omgeving in te richten voor het verfijnen van AI-modellen op Ollama.
• Datasetten voor te bereiden op het verfijnen van supervisie en versterkende leerprocessen.
• AI-modellen te optimaliseren voor prestaties, nauwkeurigheid en efficiëntie.
• Aangepaste modellen in productieomgevingen te implementeren.
• Modelverbeteringen te evalueren en de robuustheid te waarborgen.

Deze door een instructeur geleide, live training in Nederland (online of op locatie) is bedoeld voor zakelijke professionals op beginner niveau, klantondersteuning teams en tech enthusiasts die de basisprincipes van Claude AI willen begrijpen en deze willen benutten voor zakelijke toepassingen.

Aan het einde van deze training zullen de deelnemers in staat zijn om:

• De mogelijkheden en use cases van Claude AI te begrijpen.
• Claude AI effectief op te zetten en ermee te communiceren.
• Bedrijfsworkflows te automatiseren met behulp van conversatie-AI.
• Klantbetrokkenheid en ondersteuning te verbeteren met AI-gestuurde oplossingen.

LangGraph is a framework for building stateful, multi-actor LLM applications as composable graphs with persistent state and control over execution.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and operate LangGraph-based finance solutions with proper governance, observability, and compliance.

By the end of this training, participants will be able to:

• Design finance-specific LangGraph workflows aligned to regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph state and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems for performance, cost, and SLAs.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph is a framework for building graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at beginner-level developers, prompt engineers, and data practitioners who wish to design and build reliable, multi-step LLM workflows using LangGraph.

By the end of this training, participants will be able to:

• Explain core LangGraph concepts (nodes, edges, state) and when to use them.
• Build prompt chains that branch, call tools, and maintain memory.
• Integrate retrieval and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph apps for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises on design, testing, and evaluation.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph enables stateful, multi-actor workflows powered by LLMs with precise control over execution paths and state persistence. In healthcare, these capabilities are crucial for compliance, interoperability, and building decision-support systems that align with medical workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

By the end of this training, participants will be able to:

• Design healthcare-specific LangGraph workflows with compliance and auditability in mind.
• Integrate LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, ICD).
• Apply best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications in healthcare production settings.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises with real-world case studies.
• Implementation practice in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph is a framework for building stateful, multi-actor LLM applications as composable graphs with persistent state and precise control over execution.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and operate LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.

By the end of this training, participants will be able to:

• Design legal-specific LangGraph workflows that preserve auditability and compliance.
• Integrate legal ontologies and document standards into graph state and processing.
• Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production with observability and cost controls.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph is a framework for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

By the end of this training, participants will be able to:

• Design graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks for robust execution.
• Integrate retrieval, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

LangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

By the end of this training, participants will be able to:

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance and delivery outcomes.

Format of the Course

• Interactive lectures and group discussions.
• Hands-on labs implementing email workflows and content pipelines.
• Scenario-based exercises on personalization, segmentation, and branching logic.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Deze door een instructeur geleide, live training (online of ter plaatse) is gericht op beginnende professionals die Ollama willen installeren, configureren en gebruiken voor het uitvoeren van AI-modellen op hun lokale machines.

Aan het einde van deze training kunnen de deelnemers:

• De fundamenten van Ollama en zijn mogelijkheden begrijpen.
• Ollama instellen voor het uitvoeren van lokale AI-modellen.
• LLMs implementeren en interageren met behulp van Ollama.
• Prestatie en brongebruik optimaliseren voor AI-werkbelastingen.
• Toepassingen voor lokale AI-implementatie in verschillende sectoren verkennen.