TinyML in Healthcare: AI on Wearable Devices Training Course

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

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

• Understand 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 ethical AI practices.

This instructor-led, live training in Turkey (online or onsite) is designed for intermediate-level healthcare professionals who aim to implement AI and AR/VR solutions for medical education, surgical simulations, and rehabilitation programs.

Upon completion of this training, participants will be capable of:

• Grasping how AI enhances AR/VR experiences within the healthcare domain.
• Utilizing AR/VR for surgical simulations and medical education.
• Implementing AR/VR tools for patient rehabilitation and therapy.
• Investigating the ethical and privacy issues associated with AI-enhanced medical instruments.

This instructor-led, live training in Turkey (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 live, instructor-led training in Turkey (online or on-site) is tailored for intermediate-level healthcare professionals and data scientists aiming to understand and deploy AI technologies in healthcare environments.

Upon completing this training, participants will be able to:

• Recognize primary healthcare challenges that AI solutions can resolve.
• Evaluate the influence of AI on patient safety, care quality, and medical research.
• Grasp the connection between AI technologies and healthcare business strategies.
• Apply core AI principles to real-world healthcare situations.
• Construct machine learning models for the analysis of medical data.

This instructor-led course in Turkey empowers advanced professionals to architect, optimize, and launch complete TinyML pipelines. Learners will acquire the ability to acquire data, train energy-efficient models, and validate real-world applications through hands-on lab work.

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

Upon completing this training, participants will be able to:

• Fine-tune AI models using healthcare datasets such as electronic medical records (EMRs), imaging data, and time-series information.
• Implement transfer learning, domain adaptation, and model compression strategies within medical applications.
• Tackle issues related to privacy, algorithmic bias, and regulatory compliance during model development.
• Deploy and oversee fine-tuned models in practical healthcare settings.

This instructor-led live training in Turkey (online or onsite) is designed for beginner 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 Turkey (online or onsite) is designed for intermediate to advanced healthcare professionals, medical researchers, and AI developers who wish to apply multimodal AI to medical diagnostics and healthcare applications.

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

• Grasp the significance of multimodal AI in contemporary healthcare.
• Combine structured and unstructured medical data to support AI-driven diagnostics.
• Utilize AI techniques to evaluate medical images and electronic health records.
• Build predictive models for disease diagnosis and therapeutic recommendations.
• Deploy speech and natural language processing (NLP) tools for medical transcription and patient engagement.

This live session in Turkey empowers healthcare practitioners and IT teams to implement Ollama for local LLM execution. Participants will learn to embed AI into clinical workflows, tailor models for specialized tasks, and maintain rigorous data privacy and regulatory compliance within protected healthcare settings.

This instructor-led, live training in Turkey (available online or on-site) 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.

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

• Understand the fundamentals of prompt engineering in healthcare.
• Use 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.