Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
The Data Science for Public Health course is a free, beginner-friendly self-paced program designed to introduce learners to how data is used to understand health trends, support public health decisions, and improve community health outcomes. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The Data Science for Public Health course is a free, beginner-friendly self-paced program designed to introduce learners to how data is used to understand health trends, support public health decisions, and improve community health outcomes.
📋 Course Objectives
1. Translate Artificial Intelligence theory into practical, reproducible analysis.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• A portfolio-grade Artificial Intelligence deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Introduction to Data Science in Public Health
What is Data Science? • Role of Data in Public Health • Public Health vs Clinical Healthcare Data • Applications of Data Science in Health Systems
Understanding Public Health Data
Types of Public Health Data • Disease, Population, Survey, and Hospital Data • Data Quality and Privacy Basics • Introduction to Health Indicators
Analyzing Health Trends
Understanding Disease Patterns • Basic Descriptive Analysis • Visualizing Public Health Data • Interpreting Health Data Insights
Applications in Public Health
Disease Surveillance and Outbreak Monitoring • Health Risk Assessment • Planning Prevention and Awareness Programs • Data-Driven Public Health Decision-Making
Future Scope and Learning Path
Data Science in Epidemiology and Health Policy • AI and Predictive Analytics in Public Health • Career Opportunities in Health Data Analytics • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Data Science |
| Covered Tool / Platform | Public Health Data |
| Covered Tool / Platform | Health Analytics |
| Covered Tool / Platform | Data Visualization |
| Covered Tool / Platform | Disease Surveillance |
Frequently Asked Questions
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