TinyML in Healthcare: AI on Wearable Devices Training Course

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

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

• Grasp the significance of AI agents in healthcare and diagnostic processes.
• Create AI models for medical image analysis and predictive diagnostics.
• Integrate AI systems with electronic health records (EHR) and clinical workflows.
• Adhere to healthcare regulations and ethical AI standards.

This instructor-led, live training in Sweden (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 Sweden (online or on-site) 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 in Sweden (online or onsite) is aimed at 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 training in Sweden provides advanced professionals with the expertise to design, optimize, and deploy complete TinyML pipelines. Participants will gain the ability to collect data, train low-power models, and test real-world applications through practical labs.

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

Upon completing this training, participants will be able to:

• Comprehend the role and advantages of Edge AI in healthcare.
• Create and deploy AI models on edge devices for healthcare applications.
• Integrate Edge AI solutions into wearable devices and diagnostic tools.
• Design and implement patient monitoring systems using Edge AI.
• Address ethical and regulatory aspects in healthcare AI applications.

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

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

• Fine-tune AI models on healthcare datasets, including EMRs, imaging, and time-series data.
• Apply transfer learning, domain adaptation, and model compression in medical contexts.
• Address privacy, bias, and regulatory compliance in model development.
• Deploy and monitor fine-tuned models in real-world healthcare environments.

This instructor-led, live training in Sweden (online or onsite) is designed for beginner to intermediate-level healthcare professionals, data analysts, and policy makers who wish to comprehend and implement generative AI solutions in the context of healthcare.

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

• Describe the core principles and practical applications of generative AI in healthcare.
• Identify opportunities where generative AI can improve drug discovery and personalized medicine.
• Apply generative AI techniques to medical imaging and diagnostic processes.
• Evaluate the ethical implications of using AI in medical environments.
• Formulate strategies for integrating AI technologies into healthcare systems.

This instructor-led, live training in Sweden (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 live training in Sweden enables healthcare professionals and IT teams to implement Ollama for local LLMs. Participants will learn to embed AI into clinical workflows, adapt models for specialized tasks, and maintain rigorous data privacy and regulatory standards within secure healthcare settings.

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

Upon completing this training, participants will be able to:

• Grasp the core principles of prompt engineering within the healthcare context.
• Utilize AI prompts for clinical documentation and patient communication.
• Harness AI capabilities for medical research and literature reviews.
• Improve drug discovery and clinical decision-making through AI-driven prompts.
• Adhere to regulatory and ethical standards in healthcare AI applications.