TinyML in Healthcare: AI on Wearable Devices Training Course

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

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

• Grasp the role of AI agents in healthcare and diagnostics.
• Develop AI models for medical image analysis and predictive diagnostics.
• Integrate AI with electronic health records (EHR) and clinical workflows.
• Ensure compliance with healthcare regulations and adhere to ethical AI practices.

This live, instructor-led training in South Korea (online or on-site) is tailored for intermediate-level healthcare professionals seeking to apply AI and AR/VR solutions for medical training, surgical simulations, and rehabilitation.

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

• Comprehend how AI enhances AR/VR experiences within the healthcare sector.
• Utilize AR/VR technologies for surgical simulations and medical training.
• Implement AR/VR tools effectively in patient rehabilitation and therapy.
• Examine the ethical and privacy issues associated with AI-enhanced medical devices.

This instructor-led live training in South Korea (online or onsite) is tailored for intermediate-level data scientists and healthcare professionals who intend to leverage AI for advanced healthcare applications via Google Colab.

By the conclusion 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 South Korea (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 expert-led course in South Korea empowers advanced professionals to architect, optimize, and execute full-scale TinyML workflows. Through practical lab environments, participants will master data acquisition, low-power model training, and real-world application testing.

This instructor-led live training in South Korea (online or onsite) targets healthcare professionals and researchers who aim to leverage ChatGPT to enhance patient care, streamline workflows, and improve healthcare outcomes.

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

• Grasp the fundamentals of ChatGPT and its applications in healthcare.
• Use ChatGPT to automate healthcare processes and patient interactions.
• Deliver accurate medical information and support to patients through ChatGPT.
• Apply ChatGPT for medical research and data analysis.

This instructor-led, live training in South Korea (online or onsite) is designed for intermediate-level healthcare professionals, biomedical engineers, and AI developers who want to leverage Edge AI for innovative healthcare solutions.

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

• Grasp the role and advantages 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 guided, live training in South Korea (online or on-site) is designed for intermediate to advanced medical AI developers and data scientists who aim to adapt 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 able to:

• Fine-tune AI models using healthcare datasets including EMRs, imaging, and time-series data.
• Utilize transfer learning, domain adaptation, and model compression techniques within medical applications.
• Manage privacy concerns, bias issues, and regulatory compliance during model development.
• Deploy and monitor fine-tuned models effectively in real-world healthcare settings.

This instructor-led, live training in South Korea (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.

This instructor-led, live training in South Korea (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 South Korea empowers healthcare practitioners and IT teams to deploy Ollama for local LLMs. Discover how to weave AI into clinical workflows, adapt models for specialized tasks, and maintain rigorous data privacy and regulatory compliance within secure healthcare settings.

This instructor-led, live training in South Korea (online or onsite) is designed for intermediate-level healthcare professionals and AI developers seeking to apply prompt engineering techniques to improve medical workflows, research efficiency, and patient outcomes.

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

• Grasp the fundamentals of prompt engineering in healthcare.
• Utilize AI prompts for clinical documentation and patient interactions.
• Leverage AI for medical research and literature review.
• Enhance drug discovery and clinical decision-making with AI-driven prompts.
• Ensure compliance with regulatory and ethical standards in healthcare AI.