1
Fundamentals of AI/ML/DL
Explain the fundamentals of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in the healthcare context.
Learning Outcomes
2
Applications in Care Delivery
Identify key AI technologies and assess their applications in clinical diagnostics, hospital operations, and patient engagement.
3
Tool Evaluation & Compliance
Evaluate AI tools for healthcare by analyzing data requirements, integration feasibility, and compliance with regulations.
4
Applied AI in Healthcare
Apply AI-driven methods to improve patient care, optimize resources, and enable preventive healthcare.
5
Ethics, Law & Policy (India)
Recognize ethical, legal, and policy considerations for AI in healthcare within India’s regulatory framework.
6
Case Studies & Limits
Interpret case studies and real-world examples to understand the impact and limitations of AI in healthcare.
Program structure
Lesson Plan
5 modules • 51hours total length
Module 1: Foundations of AI in Healthcare
Module 1: Foundations of AI in Healthcare
What you'll learn
- Defining AI, ML, and DL in the healthcare context
- Tracing the evolution of AI in medicine from expert systems to modern models
- Analyzing healthcare data types and interoperability standards (HL7, FHIR)
- Applying core AI technologies like computer vision, NLP, and predictive analytics
- Evaluating benefits, challenges, and pitfalls of healthcare AI adoption
- Building a basic AI-enabled healthcare data pipeline
Skills you'll gain
AI FundamentalsHealthcare DataInteroperabilityComputer VisionClinical NLPPredictive AnalyticsData Governance
Module 2: Clinical Applications & Diagnostics
Module 2: Clinical Applications & Diagnostics
What you'll learn
- Applying AI to radiology, pathology, and imaging workflows
- Evaluating AI-powered diagnostic tools and triage systems
- Comparing AI vs clinician accuracy in early disease detection
- Leveraging genomics and AI for precision medicine and drug discovery
- Integrating AI into clinical workflows while addressing alert fatigue
- Validating AI models through trials, audits, and regulatory frameworks
Skills you'll gain
Medical Imaging AIClinical DiagnosticsGenomics AnalyticsDrug Discovery AIWorkflow IntegrationModel ValidationRegulatory Awareness
Module 3: Hospital & Healthcare Operations Optimization
Module 3: Hospital & Healthcare Operations Optimization
What you'll learn
- Optimizing hospital resources with AI-driven staff and bed scheduling
- Applying predictive analytics to supply chain and inventory management
- Improving patient flow with wait-time prediction and discharge planning
- Enhancing financial performance via claims automation and fraud detection
- Using AI for quality improvement, infection control, and incident prevention
- Building ROI and business cases for AI in healthcare operations
Skills you'll gain
Operations AnalyticsResource PlanningPatient Flow AISupply Chain OptimizationHealthcare Finance AIQuality DashboardsROI Analysis
Module 4: Patient Engagement & Preventive Care
Module 4: Patient Engagement & Preventive Care
What you'll learn
- Designing AI-powered chatbots and translation tools for patient communication
- Applying wearable and IoT data for chronic care and telemedicine support
- Building personalized risk prediction and AI-driven wellness recommendations
- Leveraging conversational AI for mental health support and early detection
- Enhancing adherence with reminders, nudges, and inclusive UX
- Using AI to support patient education and community health programs
Skills you'll gain
Patient EngagementChatbotsRemote MonitoringPersonalized CareMental Health AIUX for HealthcarePreventive Analytics
Module 5: Ethics, Compliance & Future Trends
Module 5: Ethics, Compliance & Future Trends
What you'll learn
- Interpreting global and Indian data privacy regulations for healthcare AI
- Analyzing fairness, bias, and inclusivity challenges in clinical AI models
- Evaluating regulatory frameworks and healthcare AI standards (WHO, ISO)
- Applying generative AI to documentation, drug development, and automation
- Designing governance structures for model monitoring and responsible AI adoption
- Assessing vendors through procurement and due diligence practices
Skills you'll gain
Ethical AIData PrivacyHealthcare RegulationsBias MitigationResponsible AIGenerative AIVendor Evaluation
