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Format: Live instructor-led online training via Zoom / Microsoft Teams
The Generative AI for Healthcare Professionals Training Course is a comprehensive professional development program designed to equip physicians, nurses, pharmacists, dentists, radiologists, laboratory scientists, hospital administrators, healthcare managers, clinical researchers, public health specialists, health informatics professionals, biomedical engineers, healthcare educators, policy makers, and digital health practitioners with advanced knowledge and practical skills in the application of Generative Artificial Intelligence (GenAI) across modern healthcare systems. The course explores the use of Large Language Models (LLMs), Generative AI platforms, clinical documentation automation, AI-assisted diagnostics, medical content generation, clinical decision support, predictive analytics, precision medicine, patient engagement, healthcare workflow automation, medical education, healthcare research, and responsible AI implementation. Participants will acquire practical competencies to integrate Generative AI into healthcare organizations while improving patient outcomes, operational efficiency, clinical productivity, healthcare innovation, and evidence-based decision-making.
Generative AI is transforming healthcare by enabling intelligent clinical documentation, automated medical coding, AI-assisted diagnosis, personalized treatment planning, medical image interpretation, virtual health assistants, research automation, patient communication, drug discovery, healthcare knowledge management, and operational optimization. Healthcare institutions worldwide are adopting Generative AI technologies to improve service quality, reduce administrative burden, enhance diagnostic accuracy, accelerate research, optimize healthcare resource utilization, strengthen patient safety, and support precision healthcare delivery. This course provides practical methodologies for implementing Generative AI solutions while addressing ethical AI governance, healthcare data privacy, cybersecurity, bias mitigation, regulatory compliance, transparency, explainability, and responsible use of AI technologies within clinical and healthcare environments.
The training integrates internationally recognized frameworks and best practices including the WHO Guidance on Ethics and Governance of Artificial Intelligence for Health, Responsible AI Principles, Health Information Systems, Electronic Health Records (EHR), Clinical Decision Support Systems (CDSS), FHIR interoperability standards, Machine Learning, Large Language Models (LLMs), Natural Language Processing (NLP), Generative AI Applications, Healthcare Data Governance, Cybersecurity Frameworks, HIPAA privacy principles, GDPR data protection concepts, ISO health information standards, and digital health transformation frameworks. Through practical demonstrations, AI-powered healthcare applications, prompt engineering exercises, simulation laboratories, collaborative learning, healthcare innovation workshops, and real-world healthcare case studies, participants develop practical competencies required to successfully implement and manage Generative AI solutions across hospitals, clinics, research institutions, ministries of health, humanitarian health programs, academic medical centers, and private healthcare organizations.
Upon successful completion of this course, participants will be able to identify high-value Generative AI opportunities within healthcare organizations, design AI-enabled healthcare workflows, develop effective prompt engineering techniques, automate clinical documentation, enhance clinical decision support, improve patient communication, strengthen healthcare data governance, evaluate AI risks and ethical considerations, monitor AI performance, and develop strategic implementation roadmaps for sustainable digital health transformation. The course combines expert facilitation, hands-on AI applications, practical simulations, healthcare innovation projects, collaborative workshops, organizational assessments, and action-oriented case studies to ensure participants acquire immediately applicable knowledge for improving healthcare delivery through Generative AI technologies.
1. Understand the principles and applications of Generative AI in healthcare.
2. Apply Large Language Models (LLMs) and prompt engineering for clinical practice.
3. Utilize Generative AI for clinical documentation and healthcare workflow automation.
4. Improve clinical decision-making using AI-assisted healthcare solutions.
5. Strengthen healthcare research, medical education, and knowledge management using AI.
6. Address ethical, legal, cybersecurity, and regulatory considerations for healthcare AI.
7. Evaluate healthcare organizational readiness for Generative AI adoption.
8. Improve patient engagement through AI-powered communication technologies.
9. Monitor and evaluate the performance of Generative AI solutions.
10. Develop strategic implementation plans for Generative AI in healthcare organizations.
1. Enhances healthcare operational efficiency and productivity.
2. Reduces administrative workload through intelligent automation.
3. Improves clinical documentation quality and accuracy.
4. Strengthens evidence-based clinical decision-making.
5. Enhances patient engagement and communication.
6. Accelerates healthcare innovation and digital transformation.
7. Improves healthcare data management and knowledge sharing.
8. Supports compliance with ethical AI and healthcare governance frameworks.
9. Strengthens organizational competitiveness through AI-enabled healthcare services.
10. Promotes continuous innovation, workforce development, and organizational resilience.
This course is designed for physicians, nurses, pharmacists, dentists, radiologists, laboratory scientists, hospital administrators, healthcare executives, clinical researchers, public health professionals, biomedical engineers, healthcare IT specialists, health informatics professionals, healthcare educators, policy makers, healthcare consultants, digital health innovators, AI developers, insurance professionals, humanitarian health practitioners, medical students, and professionals responsible for healthcare management, digital transformation, clinical services, research, and healthcare innovation.
· Introduction to Generative AI and Large Language Models (LLMs)
· Healthcare applications of Generative AI
· Prompt engineering fundamentals
· Clinical AI workflows
· Digital healthcare transformation
· General Case Study: Developing a Generative AI adoption strategy for a healthcare organization
· AI-assisted clinical documentation
· Clinical decision support systems
· Medical content generation
· Diagnostic assistance
· Patient communication automation
· General Case Study: Implementing AI-powered clinical documentation to improve healthcare efficiency
· AI for healthcare research
· Medical literature summarization
· Medical education and training
· Knowledge management
· Healthcare data analytics
· General Case Study: Utilizing Generative AI to accelerate healthcare research and medical education
· Responsible AI principles
· Ethical AI implementation
· Healthcare data privacy
· Cybersecurity and risk management
· Regulatory compliance and governance
· General Case Study: Developing governance frameworks for responsible AI implementation in hospitals
· AI implementation strategies
· Organizational readiness assessment
· Change management
· Workforce development
· AI performance monitoring
· General Case Study: Managing organizational transformation through Generative AI implementation
· Emerging Generative AI technologies
· Healthcare innovation ecosystems
· AI strategy development
· Continuous improvement
· Enterprise AI implementation planning
· General Case Study: Developing a comprehensive Generative AI roadmap integrating clinical documentation automation, decision support, healthcare research, patient engagement, AI governance, cybersecurity, workforce development, and digital healthcare transformation
1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, hands-on Generative AI demonstrations, prompt engineering workshops, healthcare simulations, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
4. Certification: Upon successful completion of training, participants will receive a Certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and course content can be adjusted to fit the required number of training days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, airport pickup, freight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after successful completion of the course.
11. Group Discounts: Register as a group of more than two participants and enjoy discounts ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon to the Foscore Development Center account to facilitate adequate preparation for the training.
13. Contact Us: For inquiries, please contact training@fdc-k.org or call +254712260031.
14. Website: Visit www.fdc-k.org for more information.