M.Sc. Digital Epidemiology
Program Overview
Introduction to the Prasanna School of Public Health
The Prasanna School of Public Health offers a range of programs designed to equip students with the skills and knowledge necessary to succeed in the field of public health.
Programs Offered
- Bachelor of Public Health (Honours)
- Master of Public Health (MPH)
- Master of Hospital Administration (MHA)
- Master of Social Work (MSW)
- MSc in Biostatistics
- MSc in Data Science
- MSc in Digital Epidemiology
- MSc in Health Technology Assessment
- Certificate Courses
M.Sc. in Digital Epidemiology
Programme Overview
The MSc Programme in Digital Epidemiology is designed to equip students with the skills and knowledge to analyze dynamic and large-scale epidemiological and non-epidemiological data. This program aims to achieve data-driven, evidence-informed policy impacts for the global community.
Programme Objectives
- Methodological Expertise: Develop proficiency in designing efficient and scalable algorithms for processing, mining, and analyzing big data in epidemiology.
- Strong Foundations: Provide a solid grounding in the multi-disciplinary facets of epidemiology, including statistical methods and computational techniques.
- Data-Driven Research: Foster the ability to conduct evidence-based research and development using advanced computational capabilities.
Curriculum Overview
- Probability and Probability Distributions
- Epidemiology
- Computational Mathematics
- Biostatistical Inference
- Linear Regression Models
- Categorical Data Analysis and Logistic Regression Models
- Clinical Trials
- Disease Modelling and Spatial Modelling
- Programming with R and Python
- Data Management and Data Warehousing
- Data Processing Techniques
- Digital Infrastructure
- Digital Innovation Methods
- Digital Monitoring and Evaluation
- Digital Communication
- Digital Legislation and Policy
- Machine Learning Methods
- Deep Learning and Text Mining
- Health Technology Assessment
- Certification in Research Methodology and Health Informatics
Duration
The program is a two-year full-time course with a semester-based curriculum, including a full semester dedicated to project/thesis work and internship.
Eligibility Criteria
Graduates with the following qualifications (with a minimum of 60% of marks or equivalent grade) from UGC Recognized Universities may apply for the MSc (Data Science) programme:
- BSc. in Statistics, Mathematics, or Computer Science
- BE/B. Tech/BCA
- Any other Graduation with a minimum of two years of learning of Mathematics or Statistics
- Note: Programming knowledge is a prerequisite for admissions to this programme.
Selection Criteria
Selection of eligible candidates will be based on merit of rank obtained in the entrance examination and/or personal interview. In the absence of entrance examination/interview, the merit of rank is prepared by using the grade obtained in Mathematics and/or Statistics and/or Computer Science in the qualifying examinations.
Placement Assistance
The department prepares students for a promising career in the domains of health care technology, e-health governance, policy think tanks along with research and academia. Through industry-academia collaborations, the department provides placement assistance to the students on successful completion of the course.
Facilities
- Healthcare: Access to hospital facilities gives students hands-on training.
- Innovation Centre: State-of-the-art Innovation Centre facilitates multi-disciplinary research.
- Labs: Laboratories give students the opportunity for practical experience.
- Sports & Fitness: World-class facilities with courts for badminton, tennis, soccer & squash, as well as a well-equipped gymnasium.
- Libraries: Libraries give students access to study resources, digital and print.
- Student Housing: Student hostels are their homes away from homes.
