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AI Applications in Public Health and Epidemiology

Data-Driven Disease Surveillance, Outbreak Prediction & Population Health Intelligence

★ 4.2 (27 ratings)26–28 Oct 202605:00 pm IST3 Days (60-90 minutes each day)Certificate
The live sessions are over · get the full recording

About This Course

This workshop introduces participants to the transformative role of Artificial Intelligence in Public Health and Epidemiology. It focuses on how AI-driven systems are revolutionizing disease surveillance, outbreak prediction, and population health monitoring. Through a structured learning approach, participants will explore how large-scale health data is used to generate actionable insights for improving global healthcare outcomes and public health decision-making.

Aim

This workshop aims to train participants in the application of artificial intelligence in public health and epidemiology, focusing on disease surveillance, outbreak prediction, health data analytics, and population-level decision-making systems.
Participants will gain conceptual and practical understanding of how AI is used to monitor disease spread, analyze epidemiological trends, support public health policy, and enable early outbreak detection using real-world datasets and accessible analytical tools.

Workshop Objectives

  • Introduce fundamentals of artificial intelligence in public health
  • Explain epidemiological data analysis and disease surveillance systems
  • Demonstrate AI-based outbreak prediction and trend analysis concepts
  • Train participants in population health data interpretation
  • Explore applications in infectious and chronic disease monitoring
  • Develop understanding of AI-driven public health decision systems
Next: Day-by-day →

Workshop Structure

📅 Day 1: Foundations of AI in Public Health & Epidemiology
Introduction to AI in public health and modern epidemiology
Principles of disease surveillance and population health monitoring
Types of epidemiological data and public health databases
AI applications in infectious and chronic disease surveillance
Overview of AI-driven public health decision support systems
🛠️ Hands-on
Explore real-world public health datasets from WHO, Our World in Data, and CDC
Visualize disease trends and interpret epidemiological indicators using Microsoft Excel
Hands-on Tools: WHO Data, Our World in Data, CDC Data Tracker, Microsoft Excel

📅 Day 2: AI-Based Disease Surveillance & Outbreak Prediction
AI concepts for outbreak prediction and disease trend analysis
Time-series analysis and epidemiological forecasting
Risk factor analysis and population health intelligence
AI in vaccination planning and healthcare resource optimization
Interpretation of epidemiological models and dashboards
🛠️ Hands-on
Analyze disease trends using Our World in Data datasets
Create basic trend visualizations and outbreak prediction charts using Microsoft Excel
Hands-on Tools: Our World in Data, Google Trends, Microsoft Excel

📅 Day 3: Precision Public Health & Future Applications
AI-driven public health surveillance frameworks
AI for precision public health and policy decision-making
Case studies in pandemic monitoring and disease control
Ethical considerations and challenges in healthcare AI
Emerging trends in AI-powered epidemiology
🛠️ Hands-on
Interpret real-world outbreak case studies using interactive public health dashboards
Design a conceptual AI-based disease surveillance workflow
Hands-on Tools: WHO Dashboard, CDC Data Tracker, Canva (Workflow Visualization)

Who Should Enrol?

This program is designed for a diverse global audience, including undergraduate and postgraduate students in life sciences, public health, and biomedical sciences, as well as Ph.D. scholars, research fellows, faculty members, and academicians. It is equally relevant for epidemiologists, public health experts, clinical researchers, and healthcare professionals, along with data scientists working in healthcare and life sciences. Additionally, professionals from the biotechnology and pharmaceutical industries, as well as policy researchers and experts in health informatics, will benefit from the workshop.

Next: Dates →

Important Dates

Registration Ends

October 26, 2026
IST 4:30 PM

Workshop Dates

October 26, 2026 – October 28, 2026
IST 05:00 pm

Workshop Outcomes

  • Understand AI applications in public health systems
  • Analyze epidemiological data and disease trends
  • Interpret outbreak prediction models conceptually
  • Apply AI thinking to population health challenges
  • Evaluate public health datasets
  • Design basic surveillance and monitoring frameworks
Next: Fees →

Recording fee

Participants in India

₹2,499

Participants outside India

$50

  • All session recordings
  • Study material
  • Certificate after completion
  • 1-year access

Get the recording

The live sessions of this workshop are over, so the live fees no longer apply. The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.

Next: FAQ →

Frequently asked questions

Will I get the recording?

Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).

What if I miss a live session?

Watch the recording in your dashboard and send your questions to the mentor through the support desk.

Do I get a certificate?

Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.

Which fee category applies to me?

Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.

How can I pay?

By card, UPI or PayPal on the payment page; international bank transfer is also available there.

What is the refund policy?

See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy

Need Help?

We’re here for you!


(+91) 120-4781-217
 WhatsApp +91 99581 61117

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