Ollama Applications in Healthcare Training Course

Advanced Ollama Model Debugging & Evaluation is a comprehensive course designed to diagnose, test, and measure model behavior during local or private Ollama deployments.

Delivered as instructor-led live training (available online or onsite), this program targets advanced AI engineers, ML Ops professionals, and QA practitioners seeking to guarantee the reliability, fidelity, and operational readiness of Ollama-based models in production environments.

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

• Systematically debug Ollama-hosted models and reliably reproduce failure modes.
• Design and execute robust evaluation pipelines utilizing both quantitative and qualitative metrics.
• Implement observability measures—such as logs, traces, and metrics—to monitor model health and detect drift.
• Automate testing, validation, and regression checks within CI/CD pipelines.

Course Format

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

Course Customization Options

• For customized training arrangements, please contact us to discuss your specific requirements.

Agentic AI represents a paradigm where intelligent systems autonomously plan, reason, and utilize tools to achieve specific objectives within defined boundaries.

This instructor-led live training, available both online and onsite, targets intermediate-level healthcare and data professionals looking to design, evaluate, and govern agentic AI solutions for clinical and operational applications.

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

• Articulate the core concepts and constraints of agentic AI within healthcare environments.
• Develop secure agent workflows that incorporate planning, memory management, and tool integration.
• Construct retrieval-augmented agents capable of processing clinical documents and knowledge bases.
• Assess, monitor, and govern agent performance using guardrails and human-in-the-loop controls.

Course Format

• Engaging lectures combined with facilitated group discussions.
• Guided laboratory sessions and code walkthroughs conducted in a sandbox environment.
• Scenario-based exercises focusing on safety protocols, evaluation methods, and governance frameworks.

Customization Options

• For teams seeking a tailored curriculum for this course, please reach out to us to make arrangements.

This instructor-led, live training in the Netherlands (online or onsite) is designed for intermediate to advanced-level healthcare professionals and AI developers who wish to implement AI-driven healthcare solutions.

Upon completing this training, participants will be able to:

• Comprehend the role of AI agents in healthcare settings and diagnostic processes.
• Create AI models tailored for medical image analysis and predictive diagnostics.
• Integrate AI systems with electronic health records (EHR) and clinical workflows.
• Ensure adherence to healthcare regulations and ethical AI standards.

This instructor-led, live training in the Netherlands (online or onsite) is aimed at intermediate-level healthcare professionals who wish to apply AI and AR/VR solutions for medical training, surgery simulations, and rehabilitation.

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

• Understand the role of AI in enhancing AR/VR experiences in healthcare.
• Use AR/VR for surgery simulations and medical training.
• Apply AR/VR tools in patient rehabilitation and therapy.
• Explore the ethical and privacy concerns in AI-enhanced medical tools.

This instructor-led, live training in the Netherlands (online or onsite) is aimed at intermediate-level data scientists and healthcare professionals who wish to leverage AI for advanced healthcare applications using Google Colab.

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

• Implement AI models for healthcare using Google Colab.
• Use AI for predictive modeling in healthcare data.
• Analyze medical images with AI-driven techniques.
• Explore ethical considerations in AI-based healthcare solutions.

This instructor-led, live training the Netherlands (online or onsite) is designed for intermediate-level healthcare professionals and data scientists who wish to understand and apply AI technologies in healthcare environments.

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

• Identify key healthcare challenges that AI can address.
• Analyze AI’s impact on patient care, safety, and medical research.
• Understand the relationship between AI and healthcare business models.
• Apply fundamental AI concepts to healthcare scenarios.
• Develop machine learning models for medical data analysis.

This instructor-led, live training in the Netherlands (online or onsite) is designed for healthcare professionals and researchers who wish to leverage ChatGPT to enhance patient care, streamline workflows, and improve healthcare outcomes.

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

• Understand the fundamentals of ChatGPT and its applications in healthcare.
• Utilize ChatGPT to automate healthcare processes and interactions.
• Provide accurate medical information and support to patients using ChatGPT.
• Apply ChatGPT for medical research and analysis.

This instructor-led, live training in the Netherlands (online or onsite) is aimed at intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI for innovative healthcare solutions.

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

• Understand the role and benefits of Edge AI in healthcare.
• Develop and deploy AI models on edge devices for healthcare applications.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems using Edge AI.
• Address ethical and regulatory considerations in healthcare AI applications.

This instructor-led, live training session in the Netherlands (online or onsite) is designed for intermediate to advanced medical AI developers and data scientists who aim to refine models for clinical diagnosis, disease prediction, and patient outcome forecasting using both structured and unstructured medical data.

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

• Fine-tune AI models on healthcare datasets, including EMRs, imaging, and time-series data.
• Implement transfer learning, domain adaptation, and model compression within medical contexts.
• Navigate privacy concerns, bias mitigation, and regulatory compliance during model development.
• Deploy and monitor fine-tuned models in practical healthcare settings.

Generative AI is a technology that creates new content such as text, images, and recommendations based on prompts and data.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level healthcare professionals who wish to use generative AI and prompt engineering to improve efficiency, accuracy, and communication in medical contexts.

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

• Understand the fundamentals of generative AI and prompt engineering.
• Apply AI tools to streamline clinical, administrative, and research tasks.
• Ensure ethical, safe, and compliant use of AI in healthcare.
• Optimize prompts to achieve consistent and accurate results.

Format of the Course

• Interactive lecture and discussion.
• Practical exercises and case studies.
• Hands-on experimentation with AI tools.

Course Customization Options

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

This instructor-led, live training in the Netherlands (online or onsite) is aimed at beginner-level to intermediate-level healthcare professionals, data analysts, and policy makers who wish to understand and apply generative AI in the context of healthcare.

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

• Explain the principles and applications of generative AI in healthcare.
• Identify opportunities for generative AI to enhance drug discovery and personalized medicine.
• Utilize generative AI techniques for medical imaging and diagnostics.
• Assess the ethical implications of AI in medical settings.
• Develop strategies for integrating AI technologies into healthcare systems.

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 in the Netherlands (online or onsite) is aimed at intermediate-level to advanced-level healthcare professionals, medical researchers, and AI developers who wish to apply multimodal AI in medical diagnostics and healthcare applications.

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

• Understand the role of multimodal AI in modern healthcare.
• Integrate structured and unstructured medical data for AI-driven diagnostics.
• Apply AI techniques to analyze medical images and electronic health records.
• Develop predictive models for disease diagnosis and treatment recommendations.
• Implement speech and natural language processing (NLP) for medical transcription and patient interaction.

This instructor-led, live training in the Netherlands (online or onsite) is designed for intermediate-level healthcare professionals and AI developers who wish to leverage prompt engineering techniques to improve medical workflows, research efficiency, and patient outcomes.

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

• Grasp the fundamental principles of prompt engineering within healthcare.
• Utilize AI prompts for clinical documentation and patient interactions.
• Apply AI technologies to medical research and literature reviews.
• Improve drug discovery and clinical decision-making through AI-driven prompts.
• Maintain compliance with regulatory and ethical standards in healthcare AI.

TinyML involves embedding machine learning capabilities into power-efficient, resource-constrained wearable and medical devices.

This instructor-led live training (available online or onsite) is designed for intermediate-level practitioners looking to implement TinyML solutions for healthcare monitoring and diagnostic applications.

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

• Design and deploy TinyML models for real-time health data processing.
• Collect, preprocess, and interpret biosensor data to generate AI-driven insights.
• Optimize models for low-power and memory-limited wearable devices.
• Evaluate the clinical relevance, reliability, and safety of TinyML outputs.

Course Format

• Lectures accompanied by live demonstrations and interactive discussions.
• Practical exercises using wearable device data and TinyML frameworks.
• Implementation tasks within a guided lab environment.

Customization Options

• For tailored training that aligns with specific healthcare devices or regulatory workflows, please contact us to customize the program.