TinyML in Healthcare: AI on Wearable Devices Training Course

This instructor-led live training in Argentina, available online or on-site, is designed for intermediate to advanced 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 live, instructor-led training in Argentina (online or in-person) is designed for intermediate healthcare professionals who aim to apply AI and AR/VR solutions for medical education, surgical simulations, and rehabilitation.

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

• Comprehending how AI improves AR/VR applications in healthcare.
• Leveraging AR/VR for surgical simulations and medical education.
• Utilizing AR/VR tools in patient rehabilitation and therapeutic contexts.
• Examining the ethical and privacy issues associated with AI-enhanced medical technologies.

This instructor-led, live training in Argentina (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 in Argentina (online or on-site) is designed for intermediate-level healthcare professionals and data scientists who wish to comprehend and implement AI technologies in healthcare environments.

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

• Identify critical 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 on Argentina empowers advanced professionals with the essential skills to design, optimize, and deploy end-to-end TinyML pipelines. Through practical labs, participants will learn to collect data, train low-power models, and test real-world applications.

This instructor-led, live training in Argentina (online or onsite) is designed for 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:

• 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 Argentina (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 Argentina (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.

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

• Fine-tuning AI models on healthcare datasets, including EMRs, imaging, and time-series data.
• Implementing transfer learning, domain adaptation, and model compression techniques within medical contexts.
• Addressing privacy concerns, bias, and regulatory compliance during model development.
• Deploying and monitoring fine-tuned models in real-world healthcare environments.

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

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

• Grasp the role of multimodal AI in contemporary healthcare.
• Combine structured and unstructured medical data for AI-driven diagnostics.
• Use AI techniques to analyze medical images and electronic health records.
• Create predictive models for diagnosing diseases and recommending treatments.
• Implement speech recognition and natural language processing (NLP) for medical transcription and patient communication.

This live training in Argentina empowers healthcare providers and IT teams to deploy Ollama for local LLMs. Participants will learn to embed AI into clinical workflows, customize models for targeted functions, and maintain rigorous data privacy and regulatory compliance within protected healthcare environments.

This instructor-led, live training in Argentina (online or on-site) is designed for intermediate-level healthcare professionals and AI developers seeking to leverage prompt engineering techniques to optimize medical workflows, enhance research efficiency, and improve patient outcomes.

Upon completion of 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.
• Apply AI tools to support medical research and literature reviews.
• Strengthen drug discovery processes and clinical decision-making using AI prompts.
• Maintain compliance with regulatory frameworks and ethical standards in healthcare AI.