TinyML in Healthcare: AI on Wearable Devices Training Course

Agentic AI represents a paradigm where artificial intelligence systems possess the capability to plan, reason, and utilize tools to achieve specific objectives within established boundaries.

This instructor-led training, available both online and onsite, is designed for intermediate-level healthcare and data teams interested in designing, evaluating, and governing agentic AI solutions for clinical and operational scenarios.

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

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

Course Format

• Interactive lectures accompanied by facilitated discussions.
• Guided labs and code walkthroughs conducted in a sandbox environment.
• Scenario-based exercises focused on safety, evaluation, and governance.

Customization Options

• For information on customizing this training, please contact us to make arrangements.

This instructor-led, live training in Brazil (online or onsite) is tailored for intermediate to advanced healthcare professionals and AI developers aiming 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 session in Brazil (online or onsite) is designed for healthcare professionals at an intermediate level who aim to utilize AI and AR/VR solutions for medical education, surgical simulations, and rehabilitation programs.

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

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

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

Upon completing this training, participants will be capable of:

• Deploying AI models for healthcare solutions using Google Colab.
• Applying AI for predictive modeling in healthcare datasets.
• Conducting medical image analysis using AI-driven methods.
• Examining ethical considerations associated with AI-based healthcare solutions.

This instructor-led, live training in Brazil (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.

TinyML refers to the deployment of optimized machine learning models on edge devices with limited resources.

This instructor-led live training (available online or on-site) is designed for advanced technical professionals aiming to design, optimize, and deploy complete TinyML pipelines.

Upon completing this training, participants will be able to:

• Gather, prepare, and manage datasets specifically for TinyML applications.
• Train and optimize models for low-power microcontrollers.
• Convert models into lightweight formats suitable for edge devices.
• Deploy, test, and monitor TinyML applications on actual hardware.

Course Format

• Instructor-led lectures and technical discussions.
• Practical labs and iterative experimentation.
• Hands-on deployment on microcontroller-based platforms.

Customization Options

• To tailor the training to specific toolchains, hardware boards, or internal workflows, please contact us to arrange it.

This instructor-led, live training in Brazil (online or onsite) is aimed at 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 Brazil (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 Brazil (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 conclusion of this training, participants will be able to:

• Fine-tune AI models using healthcare datasets, including electronic medical records (EMRs), imaging data, and time-series information.
• Implement transfer learning, domain adaptation, and model compression techniques within medical contexts.
• Address challenges related to privacy, bias, and regulatory compliance during model development.
• Deploy and monitor fine-tuned models in real-world 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 Brazil (online or onsite) is designed for healthcare professionals, data analysts, and policymakers at beginner to intermediate levels 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 core principles and practical applications of generative AI in healthcare.
• Identify opportunities for generative AI to accelerate drug discovery and advance personalized medicine.
• Apply generative AI techniques to medical imaging and diagnostic processes.
• Evaluate the ethical implications of AI in clinical settings.
• Develop strategies for effectively integrating AI technologies into healthcare systems.

LangGraph empowers stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. These capabilities are vital in healthcare for ensuring compliance, interoperability, and developing decision-support systems that align with clinical workflows.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

By the end 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 a customized training for this course, please contact us to arrange.

This instructor-led, live training in Brazil (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:

• 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.

Ollama is a lightweight platform designed for running large language models locally.

This instructor-led live training (available online or onsite) is tailored for intermediate-level healthcare practitioners and IT teams seeking to deploy, customize, and operationalize Ollama-based AI solutions within clinical and administrative environments.

Upon completing this training, participants will be able to:

• Install and configure Ollama to ensure secure use in healthcare settings.
• Integrate local LLMs into clinical workflows and administrative processes.
• Customize models to align with healthcare-specific terminology and tasks.
• Apply best practices for privacy, security, and regulatory compliance.

Course Format

• Interactive lectures and discussions.
• Hands-on demonstrations and guided exercises.
• Practical implementation within a sandboxed healthcare simulation environment.

Course Customization Options

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

This instructor-led live training in Brazil (online or onsite) targets intermediate-level healthcare professionals and AI developers who aim to leverage prompt engineering techniques to enhance 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.