Large Language Models (LLMs) Training in Amsterdam

This instructor-led, live training in Amsterdam (online or onsite) is designed for senior management professionals who wish to understand what LLMs are, explore their potential impact on business operations, and evaluate practical uses of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks like content creation, data summarization, and decision support.

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

• Understand what LLMs are and how tools like ChatGPT and Copilot function.
• Use prompt techniques to get practical, reliable results from LLMs.
• Evaluate real use cases such as email drafting, summarizing documents, and productivity automation.
• Identify investment opportunities and strategic applications for AI adoption.

This instructor-led, live training in Amsterdam (online or onsite) is designed for senior management teams seeking to understand the strategic value of LLMs and enterprise AI solutions. Participants will explore how to integrate these tools into high-level processes, craft more effective prompts, and assess opportunities for enhanced productivity and return on investment through AI adoption.

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

• Comprehend how LLMs operate and how platforms like ChatGPT and Copilot utilise them.
• Leverage prompt-based interactions to automate and speed up tasks.
• Apply AI tools to practical scenarios, including email drafting, report summarisation, and contract review.
• Assess the strategic advantages, limitations, and licensing requirements of LLM adoption.

This instructor-led, live training in Amsterdam (online or onsite) is designed for AI researchers, data scientists, and developers with intermediate to advanced proficiency who aim to understand, fine-tune, and implement Meta AI's Large Language Models for diverse NLP tasks.

Upon completing this training, participants will be able to:

• Grasp the architecture and operational mechanics of Meta AI's Large Language Models.
• Configure and fine-tune Meta AI LLMs for specific use cases.
• Develop LLM-based applications, such as chatbots, sentiment analysis tools, and text summarizers.
• Efficiently optimize and deploy large language models.

This instructor-led, live training in Amsterdam (online or onsite) is designed for intermediate-level AI professionals, business analysts, and technology leaders seeking to grasp the fundamentals of generative AI and explore LLM applications within business contexts. Participants will gain insights into transformers, prompt engineering, and the ethical implications of deploying these models in real-world scenarios.

Upon completion of this training, participants will be able to:

• Comprehend the core principles of generative AI and large language models.
• Implement and fine-tune LLMs for targeted business use cases.
• Utilize prompt engineering techniques to achieve optimal model outputs.
• Identify ethical considerations and mitigate risks associated with LLM deployment.

This instructor-led, live training in Amsterdam (online or onsite) is designed for intermediate-level AI professionals and ethicists, data scientists and engineers, and policy makers and stakeholders who wish to understand and navigate the ethical landscape of LLMs.

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

• Identify ethical issues and challenges associated with LLMs.
• Apply ethical frameworks and principles to LLM deployment.
• Assess the societal impact of LLMs and mitigate potential risks.
• Develop strategies for responsible AI development and usage.

This instructor-led, live training in Amsterdam (online or onsite) is designed for intermediate-level NLP practitioners, data scientists, content creators, translators, and global businesses seeking to utilize LLMs for language translation and multilingual content creation.

Upon completion of this training, participants will be able to:

• Grasp the core principles of cross-lingual learning and translation using LLMs.
• Implement LLMs to translate content across various languages.
• Create and manage multilingual datasets for training LLMs.
• Develop strategies to ensure consistency and high quality in translations.

This instructor-led, live training in Amsterdam (online or onsite) is aimed at intermediate-level financial analysts, data scientists, and investment professionals who wish to leverage LLMs for financial market analysis and prediction.

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

• Understand the application of LLMs in financial market analysis.
• Use LLMs to process financial news, reports, and data for market insights.
• Develop predictive models for stock prices, market trends, and economic indicators.
• Integrate LLM insights into investment decision-making processes.

This instructor-led, live training session in Amsterdam (online or onsite) is designed for intermediate-level environmental scientists, researchers, data analysts, and policy makers or advocates who wish to utilize LLMs for environmental modeling and analysis.

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

• Understand the application of LLMs in environmental science.
• Utilize LLMs to analyze and model environmental data.
• Interpret LLM outputs for environmental impact assessments.
• Communicate findings effectively to inform policy and conservation efforts.

This instructor-led live training in Amsterdam (online or on-site) is designed for intermediate VR and AR developers, game designers, and AI engineers who wish to incorporate LLMs into their applications to create more engaging and responsive environments.

Upon completion of this training, participants will be able to:

• Grasp the role of LLMs in crafting immersive VR and AR experiences.
• Build VR and AR applications that leverage LLMs for interactive dialogues and content creation.
• Integrate LLMs with VR and AR development tools to improve user engagement.
• Apply best practices for designing AI-driven narratives and interactions within virtual spaces.

This instructor-led, live training in Amsterdam (online or onsite) is designed for intermediate-level data scientists, machine learning engineers, and software developers who wish to apply Large Language Models (LLMs) to multimodal data for advanced AI applications.

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

• Understand the principles of multimodal learning with LLMs.
• Implement LLMs to process and analyze text, image, and audio data.
• Develop applications that leverage the strengths of multimodal data integration.
• Evaluate the performance of multimodal LLM systems.

This instructor-led, live training in Amsterdam (online or onsite) is aimed at intermediate-level cybersecurity professionals and data scientists who wish to utilize LLMs for enhancing cybersecurity measures and threat intelligence.

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

• Understand the role of LLMs in cybersecurity.
• Implement LLMs for threat detection and analysis.
• Utilize LLMs for security automation and response.
• Integrate LLMs with existing security infrastructure.

This instructor-led, live training in Amsterdam (online or onsite) is designed for intermediate-level data scientists and business analysts who want to leverage large language models (LLMs) to forecast trends and behaviors across various industries.

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

• Grasp the fundamentals of LLMs and their role in predictive analytics.
• Implement LLMs to analyze and forecast data within diverse sectors.
• Evaluate the effectiveness of predictive models using LLMs.
• Integrate LLMs with existing data processing pipelines.

This instructor-led, live training in Amsterdam (online or onsite) targets data scientists at an intermediate level who wish to develop a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

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

• Understand the components and functionality of transformer models.
• Optimize and fine-tune LLMs for specific tasks and applications.
• Understand the core principles and methodologies of reinforcement learning.
• Learn how reinforcement learning techniques can enhance the performance of LLMs.

This guided, live training in Amsterdam (online or on-site) is designed for intermediate content creators, marketers, and educational technologists who want to leverage LLMs to generate high-quality, diverse, and engaging content across various sectors.

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

• Comprehend LLM capabilities and their application in content generation.
• Configure and use LLMs to create various types of content.
• Apply best practices for prompting and fine-tuning LLMs to achieve desired outputs.
• Evaluate the quality of AI-generated content and refine it for specific audiences.
• Explore advanced techniques for creative and multi-modal content generation with LLMs.

This instructor-led, live training session Amsterdam (online or onsite) is designed for educators, EdTech specialists, and researchers with diverse backgrounds who aim to harness LLMs to craft personalized educational experiences.

Upon completion of this course, participants will be able to:

• Gain insight into the architecture and functional capabilities of LLMs.
• Recognize opportunities within educational content where LLMs can enable personalization.
• Create adaptive learning platforms that employ LLMs for tailored content delivery.
• Deploy strategies driven by LLMs to boost student engagement and improve learning results.
• Assess the impact of LLMs in educational contexts and make informed decisions for improvement.

This instructor-led, live training in Amsterdam (online or onsite) is aimed at intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models like LLaMA, Mistral, and Qwen for specific business or internal applications.

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

• Understand the ecosystem and key differences between various open-source LLMs.
• Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
• Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
• Evaluate, save, and deploy fine-tuned models within secure environments.

This instructor-led, live training in Amsterdam (online or onsite) is aimed at beginner-level to intermediate-level software developers and data scientists who wish to implement LLMs in speech recognition and synthesis systems.

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

• Understand the role of LLMs in speech technologies.
• Implement LLMs for accurate speech recognition and natural-sounding speech synthesis.
• Integrate LLMs with speech recognition engines and speech synthesizers.
• Evaluate and improve the performance of speech systems using LLMs.
• Stay informed about current trends and future directions in speech technologies.

This instructor-led, live training in Amsterdam (online or on-site) targets beginner to intermediate-level customer support and IT professionals seeking to leverage LLMs for building responsive and intelligent customer service chatbots.

Upon completion of this training, participants will be able to:

• Understand the fundamentals and architecture of Large Language Models (LLMs).
• Design and integrate LLMs into customer support systems.
• Enhance the responsiveness and user experience of chatbots.
• Address ethical considerations and ensure compliance with industry standards.
• Deploy and maintain an LLM-based chatbot for real-world applications.

This instructor-led, live training in Amsterdam (online or on-site) is designed for intermediate-level data scientists and AI engineers who wish to fine-tune large language models more affordably and efficiently using techniques like LoRA, Adapter Tuning, and Prefix Tuning.

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

• Understand the theoretical underpinnings of parameter-efficient fine-tuning approaches.
• Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
• Compare performance and cost trade-offs between PEFT methods and full fine-tuning.
• Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.

This instructor-led, live training in Amsterdam (online or onsite) is designed for machine learning engineers, AI developers, and data scientists at an intermediate to advanced level who wish to learn how to utilize QLoRA to efficiently fine-tune large models for specific tasks and customizations.

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

• Understand the theory behind QLoRA and quantization techniques for LLMs.
• Implement QLoRA in fine-tuning large language models for domain-specific applications.
• Optimize fine-tuning performance on limited computational resources using quantization.
• Deploy and evaluate fine-tuned models in real-world applications efficiently.

This instructor-led, live training in Amsterdam (online or onsite) is designed for intermediate-level data and marketing professionals who want to apply LLMs to analyze and interpret public sentiment from various text sources, such as social media posts, product reviews, and customer feedback.

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

• Understand the principles of sentiment analysis and its application using LLMs.
• Preprocess and prepare datasets for sentiment analysis.
• Train and fine-tune LLMs to accurately reflect sentiment in text.
• Analyze sentiment in real-time from social media and other text sources.
• Integrate sentiment analysis findings into business strategies and decision-making processes.

This instructor-led live training in Amsterdam (online or onsite) is designed for software developers and technical writers with intermediate proficiency who wish to leverage LLMs to optimize their coding workflow and produce detailed, comprehensive documentation.

Upon completing this training, participants will be able to:

• Grasp the role of LLMs in automating code generation and software documentation.
• Leverage LLMs to generate precise and efficient code snippets and documentation.
• Incorporate LLMs into the software development lifecycle to boost productivity.
• Uphold high-quality documentation standards through automated tools.
• Navigate ethical considerations and best practices for applying AI in software development.

This instructor-led, live training in Amsterdam (online or onsite) is aimed at intermediate-level business professionals and data analysts who wish to harness the power of LLMs for extracting business insights.

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

• Understand the fundamentals and applications of LLMs in the context of business intelligence.
• Apply LLMs to analyze large datasets and extract meaningful insights.
• Integrate LLM-driven analytics into strategic business decision-making processes.
• Evaluate the ethical considerations and best practices for using LLMs in business.
• Anticipate future trends in AI and prepare for the evolving landscape of business intelligence.

This instructor-led, live training in Amsterdam (online or on-site) is aimed at intermediate to advanced developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.

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

• Set up and configure LlamaIndex for use with LLMs.
• Index and query custom datasets using LlamaIndex to enhance LLM functionality.
• Design and develop sophisticated applications that utilize LlamaIndex and LLMs.
• Understand and apply best practices for working with LLMs and LlamaIndex.
• Navigate the ethical considerations involved in deploying LLM-powered applications.

This instructor-led, live training in Amsterdam (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications.

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

• Understand the principles and components of LlamaIndex.
• Ingest and structure data for use with LLMs.
• Implement context augmentation to improve AI model performance.
• Integrate LlamaIndex into existing AI systems and workflows.

This instructor-led, live training in Amsterdam (online or onsite) is designed for intermediate-level professionals who wish to leverage prompt engineering and few-shot learning to optimize LLM performance for practical applications.

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

• Understand the principles of prompt engineering and few-shot learning.
• Design effective prompts for various NLP tasks.
• Leverage few-shot techniques to adapt LLMs with minimal data.
• Optimize LLM performance for practical applications.

This instructor-led live training (available online or onsite) targets advanced engineers, AI specialists, and localization leads aiming to implement large language model (LLM) systems for automated translation, quality evaluation, and enterprise governance.

Upon completion of this training, participants will be able to:

• Construct enterprise-grade LLM localization pipelines that integrate both open-source and proprietary models.
• Deploy automated QA workflows and quality metrics to ensure translation consistency.
• Develop governance and approval frameworks for multilingual content production.
• Implement scalable, auditable LLM-based localization systems within secure environments.

AI for SQL involves applying artificial intelligence and large language models (LLMs) to automate, optimize, and enhance the generation, execution, and interpretation of SQL queries within enterprise data environments.

This instructor-led live training (available online or on-site) targets intermediate-level data engineers and technical leads who aim to incorporate AI capabilities into their SQL workflows. This enables natural language querying, intelligent optimization, and automated data analysis.

Upon completion of this training, participants will be able to:

• Integrate LLMs such as GPT, DeepSeek, LLaMA, Qwen, and Mistral into SQL environments.
• Develop natural-language-to-SQL pipelines for conversational data access.
• Implement AI-driven query optimization and error detection mechanisms.
• Design secure, auditable AI-SQL workflows suitable for enterprise use.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

LangGraph serves as a framework for constructing stateful, multi-agent LLM applications through composable graphs, enabling persistent state management and precise execution control.

This instructor-led, live training session, available either online or onsite, is designed for intermediate to advanced professionals looking to design, implement, and manage LangGraph-based financial solutions with a focus on proper governance, observability, and compliance.

Upon completion of this training, participants will be equipped to:

• Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph state and supporting tools.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems to meet performance, cost, and SLA targets.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical applications.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To request a tailored version of this course, please contact us to arrange.

Vertex AI offers robust tools for constructing multimodal LLM workflows that unify text, audio, and image data into a cohesive pipeline. With support for long context windows and Gemini API parameters, it facilitates advanced applications in planning, reasoning, and cross-modal intelligence.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced practitioners who aim to design, build, and optimize multimodal AI workflows within Vertex AI.

Upon completion of this training, participants will be able to:

• Leverage Gemini models for handling multimodal inputs and outputs.
• Implement long-context workflows to facilitate complex reasoning.
• Design pipelines that seamlessly integrate text, audio, and image analysis.
• Optimize Gemini API parameters to enhance performance and cost efficiency.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on multimodal workflows.
• Project-based exercises applying multimodal use cases.

Customization Options

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

LangGraph facilitates stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are vital for ensuring compliance, interoperability, and building decision-support systems that align with medical workflows.

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

Upon completion 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 customized training for this course, please contact us to arrange.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and localization engineers who wish to design scalable, automated translation pipelines using both proprietary and open-source LLMs.

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

• Design and deploy translation workflows using modern LLM frameworks and APIs.
• Integrate open-source and commercial models into scalable translation systems.
• Optimize translation quality through fine-tuning, prompt engineering, and automation.
• Implement cost-efficient and compliant translation infrastructure for enterprise environments.

This instructor-led live training (available online or onsite) targets advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects who aim to optimize, debug, monitor, and operate production-grade LangGraph systems.

Upon completion of this course, participants will be able to:

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Ensure reliability through strategies such as retries, timeouts, idempotency, and checkpoint-based recovery.
• Debug and trace graph executions, inspect state data, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces, deploy to production environments, and monitor SLAs and costs effectively.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live-lab environment.

Customization Options

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

This instructor-led, live training in Amsterdam (online or onsite) is aimed at intermediate-level developers who wish to learn how to use generative AI with LLMs for various tasks and domains.

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

• Explain what generative AI is and how it works.
• Describe the transformer architecture that powers LLMs.
• Use empirical scaling laws to optimize LLMs for different tasks and constraints.
• Apply state-of-the-art tools and methods to train, fine-tune, and deploy LLMs.
• Discuss the opportunities and risks of generative AI for society and business.

Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming the way DevOps teams automate essential tasks like change tracking, test generation, and alert triage by mimicking human-like collaboration and decision-making processes.

This instructor-led, live training (available online or onsite) is designed for advanced-level engineers who want to design and implement DevOps automation workflows driven by large language models (LLMs) and multi-agent systems.

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

• Integrate LLM-based agents into CI/CD workflows to enable smart automation.
• Automate test generation, commit analysis, and change summaries using agents.
• Coordinate multiple agents to triage alerts, generate responses, and provide DevOps recommendations.
• Build secure and maintainable agent-powered workflows using open-source frameworks.

Format of the Course

• Interactive lecture and discussion.
• Ample 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.

Postgres is an advanced open-source relational database that can serve as a foundation for AI-powered systems and data intelligence applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level database professionals and developers who wish to integrate, manage, and optimize AI capabilities directly within Postgres.

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

• Set up and configure Postgres extensions for AI workloads.
• Implement embeddings and similarity search using pgvector.
• Integrate open source and proprietary LLMs with Postgres for real-time insights.
• Optimize Postgres for handling AI-driven queries and workflows.

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.

This instructor-led, live training in Amsterdam (online or on-site) targets intermediate to advanced AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications. These risks include prompt injection, data leakage, and unfiltered outputs, which are addressed by incorporating security controls such as input validation, human-in-the-loop oversight, and output guardrails.

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

• Understand the core vulnerabilities of LLM-based systems.
• Apply secure design principles to LLM app architecture.
• Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
• Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.

This instructor-led live training in Amsterdam (online or onsite) is designed for intermediate to advanced professionals looking to customize pre-trained models for specific tasks and datasets.

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

• Understand the principles of fine-tuning and its applications.
• Prepare datasets for fine-tuning pre-trained models.
• Fine-tune large language models (LLMs) for NLP tasks.
• Optimize model performance and address common challenges.

LLMs for Code Understanding, Refactoring, and Documentation is a specialized technical course dedicated to harnessing large language models (LLMs) to enhance code quality, mitigate technical debt, and streamline documentation processes for software teams.

This instructor-led live training, available either online or onsite, targets intermediate to advanced software professionals eager to utilize LLMs, such as GPT, to analyze, refactor, and document complex or legacy codebases with greater efficiency.

Upon completing this training, participants will be equipped to:

• Utilize LLMs to clarify code, dependencies, and logic within unfamiliar repositories.
• Detect and refactor anti-patterns while enhancing code readability.
• Automate the generation and maintenance of inline comments, README files, and API documentation.
• Seamlessly integrate LLM-driven insights into existing CI/CD and code review workflows.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Customization Options

• To arrange customized training for this course, please reach out to us.

This instructor-led, live training in Amsterdam (online or onsite) is tailored for intermediate-level data scientists, AI developers, and AI enthusiasts who aim to utilize LLMs for various NLP tasks and create novel, diverse content for different applications.

Upon completing this training, participants will be able to:

• Establish a development environment with LLMs and essential tools.
• Expertly perform NLU and NLI tasks with LLMs.
• Extract, infer, and utilize knowledge graphs effectively.
• Generate and manage dialogues using LLMs for conversational applications.
• Evaluate content quality and diversity generated by LLMs and generative AI.
• Apply ethical principles, ensuring fairness and responsible use of LLMs.

LangGraph is a framework designed for creating graph-structured applications leveraging Large Language Models (LLMs), enabling features such as planning, branching, tool integration, memory management, and controlled execution.

This instructor-led live training, available either online or onsite, is tailored for developers at the beginner level, prompt engineers, and data professionals looking to design and construct reliable, multi-step LLM workflows using LangGraph.

Upon completing this training, participants will be equipped to:

• Articulate core LangGraph concepts (nodes, edges, state) and determine appropriate use cases.
• Construct prompt chains capable of branching, invoking tools, and maintaining context memory.
• Incorporate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures combined with facilitated discussions.
• Guided laboratory sessions and code walkthroughs conducted within a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Course Customization Options

• To arrange customized training for this course, please contact us directly.

This instructor-led, live training in Amsterdam (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.

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

• Set up a development environment that includes a popular LLM.
• Create a basic LLM and fine-tune it on a custom dataset.
• Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
• Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.

This instructor-led live training in Amsterdam (online or onsite) is designed for observability and SRE engineers aiming to integrate LLMs and AI into their monitoring, alerting, and incident analysis workflows.

This live, instructor-led training in Amsterdam (available online or onsite) is designed for IT support professionals who want to use AI tools and automation platforms to streamline support processes, standardize responses, and reduce the burden of manual documentation.

This instructor-led live training in Amsterdam (online or onsite) is designed for intermediate-level engineers and architects seeking to utilize Tencent Hunyuan to deploy large and MoE models with lower latency, higher throughput, and improved cost control.

By the end of this training, participants will be able to: explain Hunyuan production deployment patterns, optimize inference performance, implement batching and quantization strategies, and plan scalable serving operations.

This instructor-led, live training in Amsterdam (online or onsite) targets intermediate developers, technical product teams, and AI practitioners who wish to utilize Hunyuan models to create multimodal applications for image, 3D, and video generation and distribution.

By the end of this training, participants will be able to build prompt-driven workflows, generate and assess multimodal assets, serve outputs through apps or APIs, and link Hunyuan capabilities to enterprise product stacks.

Course objectives transform software / AI engineers into legal engineers — professionals who can actually build AI for legal work (eDiscovery, review, investigations).

In two days, participants build the full core stack: ingest and extract messy real-world legal data, search and retrieve it, add retrieval-augmented generation (RAG) with citations, keep it private on a local model and prove it, run a defensible AI review with court-ready metrics, and package the result for deployment.

This instructor-led live training in Amsterdam (online or on-site) targets beginner to intermediate to advanced-level AI professionals who wish to use MCP to connect AI assistants with external tools, data, and enterprise services.

By the end of this training, participants will be able to: explain MCP concepts, identify key architecture components, set up a basic integration, and apply security good practices.

This instructor-led live training in Amsterdam (online or onsite) is designed for intermediate-level enterprise architects seeking to use the Model Context Protocol to design secure, scalable, and governable agent integration platforms for enterprise environments.

By the end of this training, participants will be able to: explain MCP architecture and enterprise patterns, design secure integration platforms, apply governance and access controls, and evaluate deployment and scaling options.

This instructor-led live training in Amsterdam (online or onsite) is designed for intermediate-level developers, architects, and platform engineers who intend to use MCP to build reliable servers and clients for enterprise deployment and operations.

By the end of this training, participants will be able to: articulate practical MCP architecture, construct production-ready integrations, deploy and observe MCP services, and apply patterns for versioning, resilience, and support.

This instructor-led live training in Amsterdam (online or onsite) targets intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects seeking to utilize sovereign AI principles and governance practices. The goal is to design AI environments that protect sensitive data, adhere to localization requirements, and reduce vendor lock-in.

By the end of this session, participants will be able to: explain sovereign AI concepts, assess hosting and governance options, define controls for prompts and logs, and develop a practical adoption roadmap.