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AI For Healthcare Professionals · LearnSpace
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AI For Healthcare Professionals

Курс от AI CERTs
Средний≈ 18.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Healthcare is transforming rapidly as AI reshapes diagnostics, patient monitoring, workflow efficiency, and clinical decision-making. The AI for Healthcare Professionals Certification delivers direct, immediately applicable skills and knowledge, empowering clinicians and healthcare workers to use AI tools safely, effectively, and confidently—no coding required. This course focuses on real clinical applications, from interpreting medical data to automating routine tasks and supporting earlier, more accurate diagnoses. You’ll explore how machine learning, predictive analytics, and healthcare automation enhance patient care across emergency, inpatient, outpatient, and administrative settings. Each module combines practical instruction with case‑based exercises that show you how to evaluate clinical AI tools, streamline documentation, reduce errors, and strengthen care quality through data‑driven insights. By the end of the course, you’ll confidently apply AI in real clinical scenarios, driving efficiency and enabling safer, more precise patient outcomes that advance your clinical practice. Enroll in the AI for Healthcare Professionals Certification Online to elevate your clinical practice with intelligent, responsible AI.

Навыки, которые вы освоите

Data-Driven Decision-MakingHealthcare Industry KnowledgeAI EnablementHealth Care Procedure and RegulationClinical PracticesClinical InformaticsArtificial Intelligence and Machine Learning (AI/ML)Health CareArtificial IntelligenceHealth AdministrationPredictive AnalyticsGenerative AI AgentsAI Workflows

Программа курса

8 модулей · 92 учебных материалов

01Module 1: Fundamentals of AI for Medical Assistants14 материалов
Navigation VideoВидеоCourse IntroductionВидеоEbook: Module 1: Fundamentals of AI for Medical AssistantsЧтениеAudiobook: Module 1: Fundamentals of AI for Medical AssistantsВидео

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AI For Healthcare Professionals
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 18.8 ч

8 модулей

Язык: Английский

Субтитры: Дари, Пушту

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Podcast: Module 1: Fundamentals of AI for Medical AssistantsВидео
1.1 Definitions of AI, Machine Learning, and Related ConceptsВидео
1.2 Basic Healthcare Examples Illustrating AI ConceptsВидео
1.3 Differences Between AI, Automation, and Traditional SoftwareВидео
1.4 How AI Supports Appointment Scheduling, Patient Triage, and DiagnosticsВидео
1.5 Benefits Such as Accuracy, Efficiency, and Patient EngagementВидео
1.6 Addressing Common Myths and Misconceptions About AI Replacing Human RolesВидео
1.7 Case Study AI-Powered Appointment Scheduling at Anglara Clinics & GuideMyTriage (GMT) for Cancer Patient RoutingВидео
ACTIVITY: HotspotPLUGIN
Quiz 1Задание
02Module 2: Data Literacy for Medical Assistants12 материалов
Ebook: Module 2: Data Literacy for Medical AssistantsЧтениеAudiobook: Module 2: Data Literacy for Medical AssistantsВидеоPodcast: Module 2: Data Literacy for Medical AssistantsВидео2.1 Structured vs. Unstructured Data in HealthcareВидео2.2 Data Sources Common in Medical SettingsВидео2.3 Ensuring Data Quality and Integrity for AI ApplicationsВидео2.4 The Importance of Accurate Data for AI-Driven DecisionsВидео2.5 Matching Different Data Types to Suitable AI Use CasesВидео2.6 Practical Exercises in Linking Data Sources to Real-World ScenariosВидео2.7 Case Study Optimizing Healthcare with Structured and Unstructured Data & The Importance of Accurate Data in AI-Driven Healthcare DecisionsВидеоACTIVITY: CarouselPLUGINQuiz 2Задание
03Module 3: AI in Patient Care Optimization12 материалов
Ebook: Module 3: AI in Patient Care OptimizationЧтениеAudiobook: Module 3: AI in Patient Care OptimizationВидеоPodcast: Module 3: AI in Patient Care OptimizationВидео3.1 Introduction to Dashboards and Simple Visualizations Charts, Graphs, TrendsВидео3.2 AI Tools for Appointment Management, Reminders, and Virtual CareВидео3.3 Improving Patient Engagement Through AI-Powered CommunicationsВидео3.4 Using AI for No-show Prediction, Health Monitoring Alerts, and Resource PlanningВидео3.5 Integrating AI Insights Into Daily Operational DecisionsВидео3.6 Simulation Exercises for Patient Load ForecastingВидео3.7 Case Study AI Chatbot for Enhancing Patient Engagement at Mount Sinai Health System & Leveraging Predictive Analytics for ER Patient Flow Management at Cleveland ClinicВидеоACTIVITY: Multiple ChoicePLUGINQuiz 3Задание
04Module 4: NLP and Generative AI in Medical Documentation11 материалов
Ebook: Module 4: NLP and Generative AI in Medical DocumentationЧтениеAudiobook: Module 4: NLP and Generative AI in Medical DocumentationВидеоPodcast: Module 4: NLP and Generative AI in Medical DocumentationВидео4.1 Basic NLP Concepts Relevant to HealthcareВидео4.2 Use Cases in Patient Queries and Administrative ChatbotsВидео4.3 Automating Documentation Notes, Summaries, and Communication WorkflowsВидео4.4 Recognizing and Managing AI Errors, Hallucinations, and BiasesВидео4.5 Introduction to Accessible NLP Tools for Medical AssistantsВидео4.6 Case Study Automating Documentation in a Large Hospital Network & Managing AI Errors and Biases in AI-Powered Diagnostic ToolsВидеоACTIVITY: Problem StatementPLUGINQuiz 4Задание
05Module 5: AI in Diagnostics and Screening10 материалов
Ebook: Module 5: AI in Diagnostics and ScreeningЧтениеAudiobook: Module 5: AI in Diagnostics and ScreeningВидеоPodcast: Module 5: AI in Diagnostics and ScreeningВидео5.1 How AI Analyses Medical Images and Symptoms for Preliminary ScreeningВидео5.2 Supporting Clinical Diagnoses With AI InsightsВидео5.3 Examples of AI Detecting Common Conditions From Patient DataВидео5.4 Hands-On Review of AI-Suggested Diagnostic InsightsВидео5.5 Case Studies Demonstrating AI Effectiveness in DiagnosticsВидеоACTIVITY: TabPLUGINQuiz 5Задание
06Module 6: Ethics, Bias, and Regulation in AI for Healthcare10 материалов
Ebook: Module 6: Ethics, Bias, and Regulation in AI for HealthcareЧтениеAudiobook: Module 6: Ethics, Bias, and Regulation in AI for HealthcareВидеоPodcast: Module 6: Ethics, Bias, and Regulation in AI for HealthcareВидео6.1 Types of Bias in AI ToolsВидео6.2 Impact of Bias on Patient Outcomes and TrustВидео6.3 Overview of Regulations Like HIPAAВидео6.4 Ethical Considerations and Best Practices for Medical AssistantsВидео6.5 Case Study Analysis of Bias and Fairness in AI-Driven CareВидеоACTIVITY: Drag and DropPLUGINQuiz 6Задание
07Module 7: Evaluating and Implementing AI Tools11 материалов
Ebook: Module 7: Evaluating and Implementing AI ToolsЧтениеAudiobook: Module 7: Evaluating and Implementing AI ToolsВидеоPodcast: Module 7: Evaluating and Implementing AI ToolsВидео7.1 Criteria for Evaluating AI Relevance and Effectiveness Accuracy, ROIВидео7.2 Steps Involved in Procurement, Pilot Testing, and IntegrationВидео7.3 Recognizing Red Flags in Vendor SolutionsВидео7.4 Strategies for Collaboration With Teams and CliniciansВидео7.5 Ensuring Smooth Transition and User Adoption in WorkflowsВидео7.6 Case Study Procurement and Early Deployment of AI Tools for Chest Diagnostics in a National Health Service SettingВидеоACTIVITY: Sequence ArrangementPLUGINQuiz 7Задание
08Module 8: Cybersecurity and Emerging Trends in AI12 материалов
Ebook: Module 8: Cybersecurity and Emerging Trends in AIЧтениеAudiobook: Module 8: Cybersecurity and Emerging Trends in AIВидеоPodcast: Module 8: Cybersecurity and Emerging Trends in AIВидео8.1 Common Cybersecurity Threats Specific to AI in HealthcareВидео8.2 Best Practices Data Encryption, Multi-Factor Authentication, Access ControlsВидео8.3 Advances Like AI in Telemedicine, Wearables, and Remote MonitoringВидео8.4 Strategies for Staying Current and Adaptable to Emerging AI TechnologiesВидео8.5 Collaboration With IT and Development Teams for Ongoing Security and InnovationВидео8.6 Case Study EY’s Strategic Transformation Adapting to Emerging AI TechnologiesВидеоCourse SummaryВидеоACTIVITY: Scenario ActivityPLUGINQuiz 8Задание