Generative AI in Healthcare: Transforming Medicine and Patient Care Training Course
Generative AI is a transformative technology that leverages machine learning models to generate new, synthetic instances of data that can be used for a variety of applications in healthcare.
This instructor-led, live training (online or onsite) is aimed at beginner-level 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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction to Generative AI
- Understanding AI and machine learning fundamentals
- Deep dive into generative models
- The landscape of generative AI in healthcare
Generative AI in Drug Discovery
- Accelerating drug design with AI
- Case studies: Success stories and challenges
- Virtual screening and predictive models
Personalized Medicine through Generative AI
- Tailoring treatments with AI
- Genomics and AI: A new era of personalization
- Ethical considerations in AI-powered personalized medicine
Advancements in Medical Imaging
- Enhancing diagnostics with generative AI
- 3D medical imaging and AI reconstruction techniques
- Improving patient outcomes with AI-assisted imaging
Real-World Applications and Future Directions
- Integrating generative AI into clinical practice
- The future of AI in patient care and management
- Final project: Proposing an AI solution for a healthcare challenge
Ethical and Societal Implications
- Navigating the ethical landscape of AI in healthcare
- Data privacy, security, and governance
- Preparing for the future: Policy and regulation
Summary and Next Steps
Requirements
- Basic understanding of machine learning concepts
- Familiarity with Python programming
- Introductory knowledge of biology and healthcare systems
Audience
- Healthcare professionals
- Data analysts
- Policy makers
Open Training Courses require 5+ participants.
Generative AI in Healthcare: Transforming Medicine and Patient Care Training Course - Booking
Generative AI in Healthcare: Transforming Medicine and Patient Care Training Course - Enquiry
Generative AI in Healthcare: Transforming Medicine and Patient Care - Consultancy Enquiry
Related Courses
AI Automation with n8n and LangChain
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.
By the end of this training, participants will be able to:
- Design and implement complex workflows using n8n's visual programming interface.
- Integrate AI capabilities into workflows using LangChain.
- Build custom chatbots and virtual assistants for various use cases.
- Perform advanced data analysis and processing with AI agents.
LangChain: Building AI-Powered Applications
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.
By the end of this training, participants will be able to:
- Understand the fundamentals of LangChain and its components.
- Integrate LangChain with large language models (LLMs) like GPT-4.
- Build modular AI applications using LangChain.
- Troubleshoot common issues in LangChain applications.
LangChain Fundamentals
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.
By the end of this training, participants will be able to:
- Grasp the fundamental principles of LangChain.
- Set up and configure the LangChain environment.
- Understand the architecture and how LangChain interacts with large language models (LLMs).
- Develop simple applications using LangChain.
Small Language Models (SLMs): Applications and Innovations
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at beginner-level to intermediate-level data scientists and developers who wish to implement and leverage Small Language Models in various applications.
By the end of this training, participants will be able to:
- Understand the architecture and functionality of Small Language Models.
- Implement SLMs for tasks such as text generation and sentiment analysis.
- Optimize and fine-tune SLMs for specific use cases.
- Deploy SLMs in resource-constrained environments.
- Evaluate and interpret the performance of SLMs in real-world scenarios.
SLMs for Educational Tech: Tailoring AI for Learning and Development
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level educational technologists, instructional designers, and AI developers in education who wish to integrate Small Language Models (SLMs) into educational platforms to enhance teaching and learning processes.
By the end of this training, participants will be able to:
- Understand the role of SLMs in educational technology.
- Design AI-driven learning experiences using SLMs.
- Implement SLMs in various educational settings.
- Evaluate the effectiveness of SLMs in learning outcomes.
SLMs for Smart Cities: Urban Planning and Management with AI
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level urban planners, city administrators, and smart city solution developers who wish to implement Small Language Models (SLMs) in smart city projects to improve urban living.
By the end of this training, participants will be able to:
- Understand the application of SLMs in smart cities.
- Integrate SLMs with urban data sets for enhanced decision-making.
- Develop strategies for deploying SLMs in urban management systems.
- Assess the impact of SLMs on urban planning and smart city solutions.
Small Language Models (SLMs) for Domain-Specific Applications
28 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level data scientists and machine learning engineers who wish to create and apply small language models tailored for specific domains such as legal, medical, and technical fields.
By the end of this training, participants will be able to:
- Understand the importance and application of domain-specific language models.
- Curate and preprocess specialized datasets for model training.
- Train and fine-tune language models for domain-specific applications.
- Evaluate and benchmark models using domain-relevant metrics.
- Deploy domain-specific language models in real-world scenarios.
Small Language Models (SLMs): Developing Energy-Efficient AI
21 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to develop energy-efficient AI solutions with small language models that are both powerful and environmentally friendly.
By the end of this training, participants will be able to:
- Understand the impact of AI on energy consumption and the environment.
- Apply model compression and optimization techniques to reduce the size and energy usage of AI models.
- Utilize energy-efficient hardware and software frameworks for AI deployment.
- Implement best practices for sustainable AI development.
- Advocate for and contribute to sustainable practices in the AI industry.
Small Language Models (SLMs) for Human-AI Interactions
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level data scientists, machine learning and AI researchers who wish to create engaging and efficient AI-powered conversational experiences with small language models.
By the end of this training, participants will be able to:
- Understand the fundamentals of conversational AI and the role of SLMs.
- Design and implement user-centric AI interactions.
- Develop and train SLMs for interactive applications.
- Evaluate and improve the effectiveness of human-AI communication using appropriate metrics.
- Deploy scalable and ethical AI-driven conversational interfaces in real-world scenarios.
Small Language Models (SLMs) for On-Device AI
21 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level IT professionals who wish to deploy small language models directly onto devices with limited processing capabilities, opening up possibilities for innovative applications in various sectors.
By the end of this training, participants will be able to:
- Understand the challenges and solutions for implementing AI on compact hardware.
- Optimize and compress AI models for efficient on-device deployment.
- Utilize modern AI frameworks and tools for on-device model implementation.
- Design and develop real-time AI applications for mobile and IoT devices.
- Evaluate and ensure the security and privacy of on-device AI systems.
Cross-Lingual LLMs
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level NLP practitioners and data scientists, content creators and translators, and global businesses who wish to use LLMs for language translation and creating multilingual content.
By the end of this training, participants will be able to:
- Understand the principles of cross-lingual learning and translation with LLMs.
- Implement LLMs for translating content between various languages.
- Create and manage multilingual datasets for training LLMs.
- Develop strategies for maintaining consistency and quality in translation.
Ethical Deployment of LLMs
7 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level AI professionals and ethicists, data scientists and engineers, and policy makers and stakeholders who wish to understand and navigate the ethical landscape of LLMs.
By the end of this training, participants will be able to:
- Identify ethical issues and challenges associated with LLMs.
- Apply ethical frameworks and principles to LLM deployment.
- Assess the societal impact of LLMs and mitigate potential risks.
- Develop strategies for responsible AI development and usage.
Introduction to Google Gemini AI
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.
By the end of this training, participants will be able to:
- Understand the fundamentals of large language models.
- Set up and use Google Gemini AI for various AI tasks.
- Implement text-to-text and image-to-text transformations.
- Build basic AI-driven applications.
- Explore advanced features and customization options in Google Gemini AI.
Google Gemini AI for Content Creation
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level content creators who wish to utilize Google Gemini AI to enhance their content quality and efficiency.
By the end of this training, participants will be able to:
- Understand the role of AI in content creation.
- Set up and use Google Gemini AI to generate and optimize content.
- Apply text-to-text transformations to produce creative and original content.
- Implement SEO strategies using AI-driven insights.
- Analyze content performance and adapt strategies using Gemini AI.
Google Gemini AI for Transformative Customer Service
14 HoursThis instructor-led, live training in Ecuador (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.
By the end of this training, participants will be able to:
- Understand the impact of AI on customer service.
- Set up Google Gemini AI to automate and personalize customer interactions.
- Utilize text-to-text and image-to-text transformations to improve service efficiency.
- Develop AI-driven strategies for real-time customer feedback analysis.
- Explore advanced features to create a seamless customer service experience.