| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Basic / Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | Data Science Public Health Data Health Analytics Data Visualization Disease Surveillance |
About the Data Science for Public Health 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.
The course explains basic concepts such as health data, disease patterns, population-level analysis, visualization, and data-driven decision-making. Learners will explore how data science supports disease surveillance, health planning, prevention programs, and public health research.
Program Highlights
• Free beginner-level public health data science course
• Online self-paced learning format
• Simple explanation of health data and analytics concepts
• Covers disease trends, visualization, and public health insights
• Real-world examples from healthcare and community health
• Suitable for students and non-technical learners
• e-Certification upon successful completion
Course Curriculum
Module 1: 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
Module 2: Understanding Public Health Data
- Types of Public Health Data
- Disease, Population, Survey, and Hospital Data
- Data Quality and Privacy Basics
- Introduction to Health Indicators
Module 3: Analyzing Health Trends
- Understanding Disease Patterns
- Basic Descriptive Analysis
- Visualizing Public Health Data
- Interpreting Health Data Insights
Module 4: Applications in Public Health
- Disease Surveillance and Outbreak Monitoring
- Health Risk Assessment
- Planning Prevention and Awareness Programs
- Data-Driven Public Health Decision-Making
Module 5: 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
Tools, Techniques, or Platforms Covered
Data Science Public Health Data Health Analytics Data Visualization Disease Surveillance
Real-World Applications
- Analyzing disease trends across populations
- Monitoring outbreaks and public health risks
- Visualizing health indicators for reports
- Supporting healthcare planning and policy decisions
- Preparing for advanced learning in epidemiology and health analytics
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, public health learners, healthcare professionals, researchers, and anyone interested in using data for health decision-making.
- It is also useful for learners from public health, medicine, nursing, pharmacy, life sciences, biotechnology, statistics, data science, and social science backgrounds.
Certification
