TinyML in Healthcare: AI on Wearable Devices Training Course

Delve into agentic AI in healthcare through this instructor-led training in Hungary. Acquire the skills to design, assess, and regulate agent workflows for clinical applications. Participants will construct retrieval-augmented agents, implement guardrails, and master governance principles via hands-on labs and scenario-based exercises.

This live, instructor-led session in Hungary (offered online or onsite) is designed for intermediate to advanced healthcare professionals and AI developers looking to implement AI-driven healthcare solutions.

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

• Comprehend the significance of AI agents in healthcare and diagnostics.
• Construct AI models for medical image analysis and predictive diagnostics.
• Integrate AI capabilities with electronic health records (EHR) and clinical workflows.
• Guarantee compliance with healthcare regulations and ethical AI standards.

This instructor-led live training in Hungary (online or in-person) is designed for intermediate-level healthcare professionals aiming to integrate AI and AR/VR solutions for medical training, surgical simulations, and rehabilitation.

By the conclusion of this program, participants will be capable of:

• Understanding how AI enhances AR/VR experiences within the healthcare field.
• Applying AR/VR for surgical simulations and medical professional training.
• Employing AR/VR tools in patient rehabilitation and therapeutic settings.
• Analyzing ethical and privacy issues related to AI-enhanced medical tools.

This live, instructor-led training in Hungary (online or onsite) is tailored for intermediate-level data scientists and healthcare professionals aiming to utilize AI for advanced healthcare applications via Google Colab.

By the conclusion of the 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 session, held in Hungary (either online or in person), is tailored for intermediate-level healthcare specialists and data scientists aiming to comprehend and implement AI technologies in medical environments.

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

• Pinpoint the major healthcare challenges that AI can help resolve.
• Evaluate the effect of AI on patient care, safety standards, and medical research.
• Comprehend the link between AI and healthcare business models.
• Utilize basic AI concepts in healthcare-related scenarios.
• Create machine learning models for the purpose of medical data analysis.

This live, instructor-led program at Hungary empowers senior professionals to architect, optimize, and roll out full-scale TinyML pipelines. Learners will gain proficiency in data acquisition, low-power model training, and real-world application testing through hands-on lab exercises.

This live, instructor-led training, available either online or on-site in Hungary, is tailored for healthcare specialists and researchers looking to harness ChatGPT for improved patient care, efficient workflows, and superior health outcomes.

After completing the training, participants will be able to:

• Understand the basic mechanisms of ChatGPT and its relevance in healthcare.
• Apply ChatGPT to automate various healthcare procedures and interactions.
• Use ChatGPT to provide patients with accurate medical information and support.
• Utilize ChatGPT for advancing medical research and analysis.

This expert-led, live session in Hungary (either online or on-site) targets mid-level healthcare experts, biomedical engineers, and AI developers seeking to harness Edge AI for cutting-edge medical applications.

By the conclusion of this program, you will be able to:

• Understand the impact and advantages of Edge AI in the medical field.
• Develop and implement AI models on edge hardware for clinical use.
• Integrate Edge AI into wearables and diagnostic instruments.
• Create and deploy Edge AI-driven patient monitoring systems.
• Manage ethical and compliance issues in medical AI.

This instructor-led live training in Hungary (online or on-site) is tailored for intermediate to advanced medical AI developers and data scientists looking to refine models for clinical diagnosis, disease prediction, and patient outcome forecasting. The course utilizes both structured and unstructured medical data to drive precision.

By the end of the program, participants will be equipped to:

• Fine-tune AI models on healthcare datasets, including EMRs, imaging, and time-series data.
• Implement transfer learning, domain adaptation, and model compression in medical scenarios.
• Manage privacy issues, reduce bias, and adhere to regulatory compliance in model development.
• Deploy and oversee fine-tuned models in real-world healthcare environments.

This instructor-led program in Hungary empowers healthcare professionals to apply generative AI and prompt engineering to clinical duties. Participants will learn to optimize workflows, maintain ethical compliance, and refine AI-generated content to ensure accurate medical outcomes.

This instructor-led, live training conducted in Hungary (either online or onsite) targets beginner to intermediate level healthcare professionals, data analysts, and policy makers seeking to grasp and apply generative AI in healthcare settings.

By the conclusion of this course, participants will be capable of:

• Explaining the fundamental principles and uses of generative AI within healthcare.
• Identifying avenues for generative AI to boost drug discovery and personalized medicine.
• Employing generative AI techniques in medical imaging and diagnostics.
• Evaluating the ethical ramifications of AI in medical contexts.
• Creating strategies for the integration of AI technologies into healthcare infrastructure.

Discover the application of LangGraph in healthcare through this live training held in Hungary, curated for professionals with intermediate to advanced expertise. Gain the skills to design stateful, compliant workflows, integrate standards like FHIR and SNOMED CT, and manage ethical and operational challenges within regulated environments.

This instructor-led, live training in Hungary (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 Hungary empowers healthcare professionals and IT teams to leverage Ollama for local LLM deployment. Participants will learn to embed AI into clinical processes, refine models for distinct tasks, and uphold rigorous data privacy and regulatory standards within protected medical environments.

This instructor-led, live training conducted in Hungary (via online or onsite delivery) is tailored for intermediate-level healthcare professionals and AI developers aiming to apply prompt engineering techniques to optimize medical workflows, enhance research productivity, and achieve superior patient outcomes.

By the end of this session, participants will have the capability to:

• Comprehend the essential aspects of prompt engineering in the healthcare sector.
• Implement AI prompts to support clinical documentation and patient engagement.
• Harness AI tools for medical research and literature analysis.
• Advance drug discovery efforts and refine clinical decisions through AI-driven prompting.
• Adhere to regulatory and ethical guidelines for AI applications in healthcare.